Systems and methods for analyzing surgical techniques

ABSTRACT

A system for assessing performance of a procedure comprises a tissue model or a tool comprising assessment indicators applied thereto, one or more image-capturing devices for capturing one or more assessment images of the assessment indicators while or after a user performs the medical procedure, and a processor configured to analyze the assessment indicators in the one or more assessment images and provide feedback to the user. A system can also comprise a tissue model, one or more image-capturing devices each configured to capture one or more images of the tissue model, and a processor configured to analyze the one or more images from the one or more image-capturing devices to determine a deformation of the tissue model and determine a force exerted on the tissue model based on the determined deformation of the tissue model.

RELATED APPLICATIONS

This patent application claims the benefit of priority to Poniatowski etal., U.S. Provisional Patent Application Ser. No. 61/642,117, entitled“METHOD FOR ANALYZING SURGICAL TECHNIQUE USING ASSESSMENT MARKERS ANDIMAGE ANALYSIS,” filed on May 3, 2012, which is herein incorporated byreference in its entirety. The subject matter of this application isalso related to Reihsen et al., U.S. Provisional Patent Application Ser.No. 61/541,547, entitled “SIMULATED, REPRESENTATIVE HIGH-FIDELITYORGANOSILICATE TISSUE MODELS,” filed on Sep. 30, 2011, to Reihsen etal., U.S. Provisional Patent Application Ser. No. 61/589,463, entitled“SIMULATED, REPRESENTATIVE HIGH-FIDELITY ORGANOSILICATE TISSUE MODELS,”filed on Jan. 23, 2012, and to Reihsen et al., U.S. application Ser. No.13/630,715, entitled “SIMULATED, REPRESENTATIVE HIGH-FIDELITYORGANOSILICATE TISSUE MODELS,” filed on Sep. 28, 2012, which are hereinincorporated by reference in their entirety.

BACKGROUND

Simulation of medical procedures is becoming a more prominent part ofmedical training. Currently, tissue models, such as animal tissue, humancadaveric tissue, or simulated, artificial tissue are used for medicaleducation. Medical students can perform surgical or other medicaltechniques on the tissue model, and their performance can be evaluatedby trainers. Automatic and quantitative analysis of performance can beused because it can permit a student to assess performance without atrainer having to observe the actual procedure and because it permitsreliable, repeatable, objective assessment. However, current methods ofautomatic analysis focus on tracking the instruments used for aprocedure, such as with positional sensors mounted to the instruments.While instrument tracking can provide an approximate measure of how wellthe procedure was done, final performance analysis can still call forinspection by a trainer, such as a proctor. Moreover, instrumenttracking can fail to recognize or evaluate the effect on the tissuemodel, such as tissue tension or tearing.

SUMMARY

The present disclosure is directed to systems and methods for analyzingand evaluating medical procedures that are performed on a tissue or atissue model. The system and method can use assessment indicators orsensors that can be analyzed by image analysis or sensor outputanalysis, or both, to provide automatic feedback to a student. Thesystem and method can be configured to determine a quantitative scorefor a particular instance of the medical procedure that a student andfaculty can use to measure performance and to track improvement overtime and can become part of the student's record.

The system and method can also use a marker material comprisingdye-impregnated or dye-infused capsules that release the dye at apre-specified pressure or force to provide an indication of when athreshold pressure or force is being applied to the tissue model.

The system and method can also use one or more cameras to view andrecord a tissue model in real time in order to determine the force beingexerted on the tissue model based on known physical characteristics ofthe tissue model, such as the dynamic modulus, Young's modulus, theelastic modulus, and the like. The system and method can also beconfigured to determine internal pressure buildup due to the calculatedapplied force and the deformation of the tissue model.

In an example, this disclosure is directed to a system for assessingperformance of a medical procedure, the system comprising a tissue modelor a tool comprising assessment indicators applied thereto, one or moreimage-capturing devices for capturing one or more assessment images ofthe assessment indicators while or after a user performs the medicalprocedure, and a processor configured to analyze the assessmentindicators in the one or more assessment images and provide feedback tothe user.

In another example, this disclosure is directed to a system forassessing performance of a procedure, the system comprising a tissuemodel, one or more image-capturing devices each configured to captureone or more images of the tissue model, and a processor configured toanalyze the one or more images from the one or more image-capturingdevices to determine a deformation of the tissue model and determine aforce exerted on the tissue model based on the determined deformation ofthe tissue model.

In yet another example, this disclosure is directed to a synthetictissue model simulating a tissue for a medical procedure, the synthetictissue model comprising a base material and capsules applied to the basematerial, the capsules being impregnated with a material, wherein thecapsules are configured to expose the material upon exposure to astimulus source exceeding a stimulus threshold.

These and other examples and features of the present system and relatedmethods will be set forth, in part, in the following DetailedDescription. This summary is intended to provide an overview of subjectmatter of the present disclosure. It is not intended to provide anexclusive or exhaustive explanation of the invention. The detaileddescription is included to provide further information about the presentdisclosure.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a diagram of an example system for assessing performance of amedical procedure.

FIG. 2 is a diagram of an example reference image of a tissue model withassessment indicators applied thereto.

FIG. 3 is a diagram of an example assessment image of a tissue modelwith assessment indicators applied thereto.

FIG. 4 is a diagram of a tissue sample with three-dimensional assessmentindicators applied therein.

FIG. 5 is a representation of assessment indicators from an assessmentimage overlaid on top of assessment indicators from a reference image.

FIG. 6 is flow diagram of an example method of assessing a medicalprocedure using the example systems of FIGS. 1-5.

FIG. 7A is a diagram of an example tissue model including a filmcomprising dye-impregnated capsules that release the dye at a specificapplied pressure.

FIG. 7B is a diagram of an example tissue model system including a toolto be used on the tissue model during a medical procedure, the toolincluding a film comprising dye-impregnated capsules that release thedye at a specific applied pressure.

FIG. 7C is a diagram of an example tissue model including an additive tothe tissue model material, the additive including dye-impregnatedcapsules that release the dye at a specific applied pressure.

FIG. 8 is a flow diagram of an example method for assessing a medicalprocedure using the example systems of FIGS. 7A-7C.

FIG. 9 is a diagram of an example deformation of an example tissuemodel.

FIG. 10 is a diagram of an example tissue model system for analyzing thepressure or force being applied to a single-layer tissue model.

FIG. 11A is a diagram of an example tissue model system for analyzingthe pressure or force being applied to a multi-layer tissue model.

FIG. 11B is a close side view of the example multi-layer tissue model ofFIG. 11A.

FIG. 12 is a flow diagram of an example method for assessing a medicalprocedure using the example systems of FIGS. 9-11.

FIG. 13 is an illustration of animate renal artery training model withblood.

FIG. 14 is an illustration of animate kidney training model forendoscopy.

FIG. 15A is an illustration of BLAST face Model with rare earth elementbased coating under normal light.

FIG. 15B is an illustration of BLAST face model with rare earth elementcoating under black light.

FIG. 15C is an illustration of BLAST face model with rare earth elementcoating under UV light.

FIG. 15D is an illustration of BLAST face model with rare earth elementcoating under IR light.

FIG. 16 is an illustration of animate ureter training model forendoscopy.

FIG. 17 is an illustration of animate hand training model for endoscopy.

DETAILED DESCRIPTION

The present disclosure is directed to systems and methods for analyzingand evaluating surgical techniques that are performed on a tissue or atissue model. The system and method can use assessment indicators orsensors embedded or present in the tissue or tissue model that can beanalyzed by image analysis or sensor output analysis, or both, toprovide automatic feedback.

The system and methods can include a tissue or tissue model withindicators or sensors, or both, that can be viewed or detected by acomputer system and analyzed after a medical procedure has beencompleted and can provide a quantitative score for the performance Thescore can be determined based on selected parameters, such aspreservation of the tissue or tissue model, tension on the tissue ortissue model, overlap of the tissue or the tissue model, approximationof the tissue or the tissue model, exposure of a portion of the tissueor the tissue model. The quantitative score can provide an objectivemeasure of performance in a specific instance of the medical procedure,or it can provide an indication of progress over time as the procedureis repeated and subsequent scores can be compared.

FIG. 1 shows an example of a system 10 that can assess performance of amedical procedure. The medical procedure can include a surgicalprocedure or a non-surgical medical procedure. In an example, the system10 includes a tissue or tissue model 12 on which the procedure will beperformed. The tissue or tissue model 12 can be actual tissue from theactual type of patient that the student is training for, such as humantissue for a medical school student, intern, or resident. The tissue ortissue model 12 can also be a material configured to simulate the actualtissue for the type of patient that the student is training for, e.g., atissue model that simulates human tissue for a medical school student,intern, or resident. For the purpose of brevity, tissue or tissue modelwill be referred to throughout this application as “tissue model,”because it is envisioned that the system and methods will most commonlybe used with simulated tissue models rather than actual living tissue.The tissue model 12 can be formerly living tissue, such as animal tissuemodels or cadaveric human tissue, or it can be an artificial tissuemodel, such as an organosilicate-based tissue, described in more detailbelow.

The tissue model 12 can include one or more assessment indicators, suchas assessment markings applied to the tissue model 12, which can providefor visual assessment of the tissue model 12. The assessment markingscan include visible assessment markings comprising a material that isvisible to the human eye under normal conditions to indicate to a user,such as a trainee or student, a proper position for an aspect of aprocedure, such as the location where a trainee should perform aparticular action, such as clipping, cutting, dissecting, or suturingthe tissue model. The visible assessment markings can include an ink ordye applied to one or more layers or surfaces of the tissue model 12.

In addition to or in place of visible assessment markings, the tissuemodel 12 can also can also include one or more assessment markings 16 ofa material that is invisible or substantially invisible under normallight so that the assessment markings 16 will not be seen by a user ofthe tissue model 12, such as a trainee or student. The assessmentmarkings 16 can be formed from an indicator material that is latentlydetectable, such as by only being visible or otherwise detectable underspecific conditions, for example when the tissue model 12 is illuminatedunder light having a specific wavelength, such as UV light. Theindicator material of the assessment markings 16 can then be made to bevisible to the trainee or an evaluator after completion of the procedureto determine the effectiveness of the procedure.

The indicator material that forms the assessment markings 16 cancomprise a coating that is sensitive to a particular wavelength or rangeof wavelengths of light. In an example, the indicator material caninclude an ultraviolet light sensitive material that fluoresces when theindicator material is exposed to UV light. For the sake of brevity, theindicator material will be described as a UV-sensitive indicatormaterial. However, a person of ordinary skill in the art can appreciatethat materials sensitive to other wavelengths of light, such as infraredlight, can be used.

The indicator material that forms the assessment markings 16 can beadded onto or into the tissue model 12, for example on oneorganosilicate layer or between organosilicate tissue layers, atspecified locations. In an example, the indicator material comprises apolymer resin that can be applied to one or more layers or surfaces ofthe tissue model 12 to form the latently-detectable assessment markings16. The indicator material that forms the assessment markings 16 can beapplied in lines, dots, or other patterns, or can be incorporated acrossan entire surface of a layer of the tissue model 12 or through an entirelayer of the tissue model 12. While performing a specified task, such asa medical procedure, the user (e.g., a trainee) can be unaware of theindicator material coating patterns on the tissue model 12 due to theirtransparent nature under normal light. Following completion of a task bythe user, an evaluation of his or her ability to perform the task can bemade by exposing the tissue model 12 under UV light where theUV-sensitive indicator material can reveal the coating pattern. In anexample, UV-sensitive coatings can be applied to fluoresce in more thanone color when exposed to UV light, such as a first color for a firstpattern of assessment markings 16, and a second color for a secondpattern of assessment markings 16.

The indicator material that forms the assessment markings 16 can becreated from UV pigments that are natural or synthetic minerals, whichcan then be added to a base material, such as a polymer resin or a basematerial of the tissue model 12, such as an organosilicate base. Thebase can then be agitated to ensure a complete homogenous mixture. Thepigments can be in a powder form. Examples of pigments which make up thecolors of blue, red, white, yellow, orange, or green can be selectedfrom the following list of minerals: adamite, agate, albite, alunite,amber, amblygonite, analcime andersonite, anglesite, anthrophyllite,apatite, aphthitalite, apoplyllite, aragonite, autunite, axinite,barite, becquerelite, boltwoodite, brucite, cahnite, calcite, caloimel,celestite, cerrusite, chondrodite, clinohedrite, corundrum, cowlesite,datolite, dioside, dypinite, espertite, eucryptite, fluorite, foshagite,gaylusite, gowerite, gypsum, halite, hanksite, hemimorphite,hydroboracite, idrialite, laumontite, magnesite, margarosanite,melanophlogite, mesolite, meta-autunite, meyerofferite, montebrasite,nahcolite, natrolite, norbergite, opal, pectolite, phosphuranylite,pirssonite, plombierite, powelite, pyrophylite, quartz, scapolite,scheelinte, smithsonite, sodalite, soddylite, sphalerite, spodumene,stilbite, strontianite, talc, thaumasite, thomsonite, tirodite,tremolite, trona, ulexite, uralolite, urannopilite, uranocirite,walstromite, wavellite, whewellite, willemite, witherite, wollastonite,wulfenite, wurtziste, xonotlite, zincite, zippeite, zircon.

Fluorescent pigments can be combined to create custom colors that canmatch the tissue, or contrast based on need. Embedment of commercial offthe shelf (COTS) indicators can also be used. An example would be ofClear Neon Black Light Paint.

In an example, photochromatic or piezochromatic materials can providefor a color change based on contact or pressure applied to a particularlocation of the tissue model 12 that can provide for a non UV-based goalfor measurement. A thermochromatic material exposed to heat can also beused, and would produce a similar effect. Chemical indicators can alsobe used using a steam, or chemical acid/base interaction and can providesimilar results.

The assessment markings 16 can be located on an outer surface of thetissue model 12, or can be located in or on one or more internal layersof the tissue model 12, or both. The location of the assessment markings16 can depend on the specific procedure being assessed. The assessmentmarkings 16 can be added within or between one or more layers of thetissue model 12 in order to provide for skill proficiency training andevaluation. The assessment markings 16 can be added as lines, dots, orother indicating patterns that can be used to indicate or determineproper performance of a particular task. For example, when evaluatingsuturing technique for the repair of a wound or incision 18, theassessment markings 16 can be formed as a grid 20 of lines 22 positionedon an outer surface of the tissue model 12 proximate to and around thelocation of the wound or incision 18. The grid 20 can be analyzed, asdescribed in more detail below, in order to assess tension on the tissuemodel 12 during suturing, overlap of the tissue model 12 at the junctureof the wound or incision 18, or approximation of the tissue model 12around the wound or incision 18. An indicator material can be applied toan entire layer or layers of the tissue model 12, e.g., so that thelayer or layers themselves can act as assessment markings 16 so that ifthe layer is exposed during the procedure, it can be detected foranalysis.

In an example, the assessment markings 16 can be arranged in atwo-dimensional pattern, such as a square geometric grid, a triangulargeometric grid, a pattern including simple or compound curves, and thelike, that can be positioned on the outer surface of the tissue model12. The two-dimensional pattern of the assessment markings 16 can beconfigured so that it will be altered by the procedure in predictableways. For example, for a suturing procedure, individual lines 22 of thegrid 20 will be deformed in predictable ways depending on the tension onthe tissue model 12 from sutures that are placed in the tissue model 12by a trainee.

FIGS. 2 and 3, described in more detail below, show an example ofassessment markings 16A on a tissue model 12A comprising atwo-dimensional pattern, such as the grid 20 of lines 22, that can beused to assess deformation of the tissue model 12A. FIG. 1 shows thetissue model 12A with a wound or incision 18 and the grid 20 before asuturing procedure has been performed. FIG. 2 shows assessment markings16A as they would appear under a UV light, where the assessment markings16A can be used as a reference for image processing. FIG. 3 shows thesame tissue model 12A after the wound or incision 18 has been repairedby sutures 24. FIG. 3 shows assessment markings 16A as they would appearunder a UV light, where the assessment markings 16A can be compared tothe reference markings of the reference image via image processing. Thegrid lines 22 can be moved as a result of the tension applied by thesutures 24. In the examples shown in FIGS. 2 and 3, the grid 20 isaltered by the suturing procedure in that a first vertical grid line 22Ahas become broken and shortened by the suturing procedure, while asecond, horizontal grid line 22B, a third, horizontal grid line 22C, anda fourth, horizontal grid line 22D have become misaligned, with one sideof each grid line 22B, 22C, 22D being shifted vertically downward on oneside of the sutured wound or incision 18 with respect to the other sideof the wound or incision 18 (FIG. 1). As described in more detail below,the alterations in specific grid lines 22, such as breaking of a gridline 22, shortening or lengthening of a grid line 22, or dis-alignmentof a grid line 22, can be analyzed to assess the effectiveness of thesuturing procedure.

The deformation of the lines 22 of the grid 20 can include changes inlength of a particular line 22, changes in angles between segments ofthe lines 22, and the orientation of a particular line 22. The length ofgrid lines 22 across a wound or incision 18 can also be used todetermine overlap of the tissue model 12A. The alignment or matching upof grid lines 22 across the wound or incision 18 can be used to assessapproximation of the repair of the wound or the incision 18.

In an example, the assessment markings 16 can comprise athree-dimensional volume of the tissue model 12, such as a specific orcomplex shape. The three-dimensional volume can simulate an unwantedmass of tissue, such as a tumor, non-cancerous growth, or other diseasedor damaged tissue that is to be removed by the medical procedure.Conversely, the three-dimensional volume can simulate a portion oftissue that is desired to be kept, such as an organ or healthy tissuesurrounding tissue that is to be removed.

FIG. 4 shows an example of a tissue model 12B having one or moreassessment markings 16B comprising a volume of the tissue model 12B thatcan simulate a portion of the tissue model 12B that is to be removed,such as a tumor or an otherwise diseased portion of tissue. Theassessment markings 16B can comprise a specified and complex volume 26of the tissue model 12B. The volume 26 can comprise pigment or dye thatis only viewable under a particular wavelength of light, such as thelight-sensitive, e.g., UV-sensitive, polymer resins described above,that is blended with the material of the tissue model 12B. The volume 26can be configured so that it is covered by other portions of the tissuemodel 12B prior to a medical procedure, where the medical procedure caninclude removal of the volume 26 by incision, excision, or dissection.If, after the procedure, any portion of the volume 26 is left behind, itcan become visible under the particular wavelength that the pigment ordye is sensitive to, such as UV light.

One or more additional volumes can be positioned in or around the firstvolume 26 in order to further assess the performance of the medicalprocedure. For example, a second volume 28 can be positioned around thefirst volume 28, wherein the second volume 28 can include a differentpigment or dye, such as a pigment or dye that appears as a differentcolor from the first pigment or dye of the first volume 26 or thatappears under a different wavelength of light than the first pigment ordye of the first volume 26. The second volume 28 can be used todetermine how much of the tissue surrounding the first volume 26 wasleft behind, in order to assess the performance of the student ortrainee in preserving or maintaining the desired tissue.

A third volume 30 can be positioned proximate to the first volume 26 andthe second volume 28 and can simulate a specific tissue, such as anorgan, that is to be avoided during the procedure. The third volume 30can include a third pigment or dye, such as a pigment or dye thatappears as a different color from the first pigment or dye of the firstvolume 26 and from the second pigment or dye of the second volume 28 orthat appears under a different wavelength of light than the firstpigment or dye of the first volume 26 and the second pigment or dye ofthe second volume 28.

Returning to FIG. 1, the system 10 can also include a device or meansfor imaging the assessment markers 16, such as a camera 32. The system10 can also include a device or means for analyzing the assessmentmarkers 16, for example a processor 34 that can analyze images or videotaken by the camera 32. The processor 34 can be one or more processors,such as one or more microprocessors, digital signal processors (DSPs),application specific integrated circuits (ASICs), field programmablegate arrays (FPGAs), programmable logic circuitry, or the like, eitheralone or in any suitable combination. The processor 34 can be configuredvia instructions or code, such as microcode, assembly language code, ahigher-level language code, or the like. The instructions or code caninclude computer readable instructions for performing various methods.The instructions or code can form portions of computer program products.The instructions or code can be tangibly stored on a memory 36, such asone or more volatile, non-transitory, or non-volatile tangiblecomputer-readable media, such as during execution or at other times.Examples of these tangible computer-readable media can include, but arenot limited to, hard disks, removable magnetic disks, removable opticaldisks (e.g., compact disks and digital video disks), magnetic cassettes,memory cards or sticks, random access memories (RAMs), read onlymemories (ROMs), and the like.

The processor 34 can be configured to analyze images or video capturedby the camera 32 in order to assess performance of a particular medicalprocedure. In an example, the processor 34 is configured to compare oneor more images or video captured by the camera 32 to one or morereference images or videos in order to determine a compliance of thepresent medical procedure to an ideal or desired outcome for the medicalprocedure.

In an example, one or more images of the tissue model 12 and theassessment markings 16 can be taken during or after the completion ofthe medical procedure being assessed. FIG. 3 is an example of anassessment image 38 taken of a tissue model 12A and the assessmentmarkings 16A after completion of a suturing procedure. As noted above,the tissue model 12A has been exposed to UV light while the image ofFIG. 3 was taken so that the assessment markings 16 are captured in theassessment image 38.

A reference image can be captured or created in order to compare to theimage 38. In an example, the reference image can be an image capturedafter an expert performed substantially the same procedure. In anotherexample, the reference image can be created as a composite or average ofa plurality of individual expert results, such as the same orsubstantially the same procedure being performing by a plurality ofexperts or an individual expert performing the same procedure aplurality of times, a combination of the two, or based on a consensusconference of experts. The plurality of images can be analyzed andcompared, such as by the processor 34, to produce an image average ofall the expert images. In another example, for a relatively simpleprocedure, such as a simple suturing procedure, the reference image cancomprise an image of the tissue model 12A and the assessment markings 16before the procedure has been performed, so that the trainee or studentcan attempt to maintain the tissue model as close to its “natural” stateas possible.

FIG. 2 shows an example of a reference image 40 that comprises thetissue model 12 in its unsutured state before a suturing procedure hasbeen performed. The reference image 40 thus can represent the “before”image of the tissue model 12A, while the assessment image 38 canrepresent the “after” image taken after the procedure has beencompleted.

In an example, the assessment image 38 can be compared to the referenceimage 40 via image processing software that is run by the processor 34.The image processing software can allow the processor 34 to firstregister the assessment image 38 and the reference image 40, and then tocompare registered images 38, 40 to determine a difference between thetwo images, and, in some examples, to provide an assessment score.

The terms “registering,” “registered,” and “registration,” as usedherein, can refer to aligning the images 38, 40 to account for anydifferences in images due to the images 38, 40 being captured underdifferent conditions or camera perspectives, such as different lightingconditions or under different angles or distances of the camera 32relative to the tissue model 12 when the images 38, 40 were taken. In anexample, in addition to the assessment markings 16, the tissue model 12can also include registration markings 42 that provide reference pointsto assist the image processing software in registering the assessmentimage 38 to the reference image 40. As shown in FIGS. 3 and 5, theregistration markings 42 can comprise a plurality of registration pointsthat are positioned at specific locations around the assessment markings16, such as five registration points being substantially evenly spacedaround a periphery of the assessment grid 20. The registration markings42 can be distinguishable from the assessment markings 16A, such as bybeing configured to appear as a different color, shape, or intensitythan the assessment markings 16A, so that the processor 34 and the imageprocessing software can recognize the difference between the assessmentmarkings 16A and the registration markings 42.

The image processing software can translate or otherwise transform theassessment image 38 so that the registration markings 42 in theassessment image 38 are substantially aligned with and are substantiallythe same size as the registration markings 42 in the reference image 40.Alternatively, the image processing software can translate or otherwisetransform the reference image 40 so that the registration markings 42 inthe reference image 40 are substantially aligned with and aresubstantially the same size as the registration markings 42 in theassessment image 38.

After registering the assessment image 38 with the reference image 40,the registered images 38, 40 can be compared by the image processingsoftware to determine the differences between the two images 38, 40. Inan example, the assessment image 38 is compared to the reference image40 by first isolating the gridlines 22 from the assessment image 38 andisolating the gridlines 22 from the reference image 40, and then byoverlaying the assessment image gridlines 22 onto the reference imagegridlines 22, or vice versa. FIG. 5 shows an example of assessmentmarkings 46A from the assessment image 38 being overlaid on top ofassessment markings 46B from the reference image 40. As can be seen inFIG. 5 by the different cross-hatching used to distinguish each set ofassessment markings 46A, 46B, much of the reference image assessmentmarkings 46B are matched or substantially matched by the assessmentimage assessment markings 46A. However, in a few areas, the referenceimage assessment markings 46B are exposed due to misalignment of theassessment image assessment markings 46A off of the reference imageassessment markings 46B. In an example, an image of the assessment imageassessment markings 46A overlaid onto the reference image assessmentmarkings 46B, or vice versa, can be displayed to the trainee to providevisual feedback to the trainee regarding the procedure.

The image processing software can be configured to determine anassessment score based on the comparison of the assessment image 38 tothe reference image 40 in order to provide a quantitative measure ofperformance. In an example, the assessment score can be calculated as apercentage of area of overlap between the isolated assessment markingsof the assessment image 38, e.g., the gridlines 22A, and the isolatedassessment markings of the reference image 40, e.g., the gridlines 22B.Other methods of determining a quantitative assessment score can be usedwithout varying from the scope of the present disclosure. For example,specific areas or location of the assessment markings can be given aweighted score so that overlap of the assessment markings between theassessment image 38 and the reference image 40 in certain areas canresult in a higher score than overlap in other areas. Similarly, theweighting of the score can result in a lack of overlap in certain areas,resulting in a lower score, e.g., a larger penalty, than lack of overlapin other areas. Moreover, parameters other than the overlap of theassessment markings between the assessment image 38 and the referenceimage 40 can be used, such as the amount of overlap at the closure ofthe wound or incision 18, or approximation of the tissue at the wound orincision 18. In an example, a model of potential outcomes for theassessment markings in the assessment image 38 can be created thatdetermines predicted outcomes, such as healing speed and scar tissueformation, wherein the model can be used to create a quantitativeassessment score.

Returning to FIG. 1, the system 10 can also include one or more sensors46 that are located on or imbedded within the tissue model 12, such as apressure sensor, a strain gauge, a deformation sensor, or a sensorcapable of determining if a plane or location has been breached by aninstrument. The sensors 46 can be located at specific locations withinthe tissue model 12 to provide additional feedback regarding performanceof the medical procedure. For example, one or more pressure sensors canbe positioned below where a dissection procedure is to be performed todetermine if a pressure exerted by the trainee onto the underlyingtissue exceeds a desired threshold that might lead to further damage,such as excessive bruising or scarring.

In an example, sensors can be positioned on or between a layer or layersof the tissue model 12 or imbedded within one or more layers of thetissue model 12 for measuring deformation of the tissue model uponcontact or collision with objects such as surgical instruments, hands ofa medical practitioner or other organs such as bones.

In an example, a piezoelectric film that can detect pressure ordeformation can be used, such as the pressure or force sensing filmssold by Tekscan, Inc. (South Boston, Mass. USA).

In an example, at least one of a strain gauge, a capacitive diaphragm,an electromagnetic inductance diaphragm, an optical strain detectionsensor, a potentiometer mechanism, a vibration sensor, an accelerometer,a dynamic switch element, and a piezoelectric sensor can be positionedon or between or imbedded within any layer of the tissue model. In anexample, the sensor can produce a voltage signal in proportion to acompression force, or a tensile mechanical stress or strain.Piezoelectric sensors, such as a piezoelectric film or fabric, can alsobe well suited for high fidelity tissues with audio in the highfrequency (e.g., greater than about 1 kHz) and ultrasound frequency(e.g., up to 100 MHz) ranges, such as for ultrasound detection.Piezoelectric sensors can be in the form of cables, films, sheets,switches, and can be amplified in a laboratory setting.

In an example, a piezoresistive sensor can be used to measuredeformation of the tissue model material at a particular location. In anexample, a piezoresistive fabric can be imbedded on, within, or betweenlayers of the tissue model to provide contact and deformation detectionwith minimal delay in response or recovery time (over 400 Hz). A smalldelay in response or recovery time allows for haptic data of theinteractions to be collected and for a dynamic response to be performed.

In an example, EeonTex flexible fabric (also known as e-fabric), sold byEeonyx Corporation (Pinole, Calif. USA) can be used as a piezoelectricsensor that can conform with three-dimensional surfaces can be used.

In an example, a sensor can be located at an expected collision site.For example, while intubating the airway of an artificial tissueanalogue, one or more sensors can be placed in at least one of anartificial tongue, an artificial larynx, an artificial pharynx,artificial vocal cords, and an artificial bronchia because theselocations are known as collision sites where damage has occurred byimproper technical or procedural technique. In an example, a sensor orsensors can be located near an incision site for the tissue model inorder to measure the depth, pressure, and forces (with direction) of anymovement of the tissue.

In an example, flow sensors can be imbedded into the tissue in order tomeasure flow rate, for example of a simulated blood flowing through thetissue model.

In an example, leak testing pressure sensors can be used to send thedecay of pressure in a closed-loop artificial artery or vein due to anaccidental or purposeful cut, incision, or needle stick of the wall ofthe model. Quantifying the amount of fluid loss can be associated withblood loss in a patient during procedures, which can be related tooutcomes and safety metrics.

FIG. 6 is a flow diagram of an example method 50 of assessingperformance of a medical procedure. The method 50 can include, at 52,applying assessment markings to a tissue model, such as the gridlines22. As described above, the assessment markings can comprise an ink,pigment, or dye that is applied to a layer or a volume of the tissuemodel. The assessment markings can be configured so that they areundetectable or substantially undetectable, such as by being invisibleor substantially invisible, while a procedure is being performed, butthat can be made to be detectable after the medical procedure iscomplete, such as by becoming visible under a specific wavelength oflight, such as UV light. At 54, an assessment image or video of thetissue model and the assessment markings can be taken after theprocedure has been performed, such as by taking a picture of the tissuemodel while it is being exposed to UV light so that the assessmentmarkings are visible in the captured image. At 56, the assessment imageor video can be compared to a reference image or video. At 58, a scorecan be created from the comparison of the assessment image or video tothe reference image or video. The score can be a quantitative scorebased on one or more measurable differences between the assessment imageand the reference image, such as a percentage of overlap area betweenthe assessment image and the reference image. The score can also beprovided by comparing the assessment image to a simulation model of thetissue that can estimate tissue outcomes, such as scarring or othertissue damage.

FIGS. 7A, 7B, and 7C each shows further examples of tissue model systemsthat can be used to assess performance during a medical procedure or amedical procedure being performed on a tissue model. Each of FIGS. 7A-7Cincludes the use of assessment indicators comprising impregnatedcapsules on or within the tissue model, or on a tool that is being usedon the tissue model during the medical procedure. The impregnatedcapsules may contain one or more materials (such as one or more dyes,one or more chemicals, one or more metals, one or more pH indicators, orone or more elements or other materials) that can respond to an externalstimulus. The impregnated capsules can be configured to expose oractivate the material impregnated within the capsule when the capsulesare exposed to the external stimulus above a predetermined stimulusthreshold. The material impregnated within the capsule can be configuredto be detectable under predetermined conditions (e.g., to become visibleonce exposed, or to be visible or otherwise detectable under specifiedconditions, such as when a particular temperature, light, or chemical isapplied to the material). Thus, the capsules can be used to determine ifand when a particular stimulus threshold has been exceeded.

For example, the capsule can be configured to release a dye materialwhen a pressure applied to the capsules is beyond a predeterminedpressure threshold, such as by being breached or bursting.Alternatively, the capsules can be configured to release or expose thematerial when exposed to other stimuli, such as:

-   -   (a) a predetermined heat source, e.g., so that the capsules        burst or expose the material when a particular temperature is        reached;    -   (b) light source, e.g., so that the capsules burst or release        the material when a particular wavelength of light is incident        upon the capsules. A structure of the capsules can also be        configured to be transparent or substantially transparent to a        particular wavelength of light, and the material within the        capsule can be activated by the same wavelength of light.    -   (c) chemical source, e.g., so that a portion of the capsules        chemically reacts with a particular chemical species to release        or expose the material. The capsule can also be configured so        that the chemically-reacting portion of the capsule reacts to        form the material. The capsule can also be configured to be        permeable to certain chemical species to pass into the capsule        and interact with the material to produce a change in the        material, such as a color change.    -   (d) electromagnetic source, e.g., so that a particular current,        charge, voltage, or electromagnetic field will cause the capsule        to expose or release the material. The electromagnetic source        can also direction act on the material to provide a change. For        example, if a metal or other magnetizable material is        impregnated within the capsules, the magnetizable material can        be configured to change orientation when exposed to a particular        electromagnetic field. The change in orientation can be detected        in much the same way that a computer hard drive is read.

The activation or exposure of the material thus can provide anindication that the particular stimuli threshold has been reached. Theindication can be visual or detectable via other means. The indicationcan also be temporary, reversible, or permanent. The encapsulatedmaterials can also act as biomimetic chromatophores to indicate thingslike bruising, changes in physiology, and the like.

As described in more detail below, the capsules can be deployed on asurface of the tissue model or the tool being applied to the tissuemodule, or within the tissue model. Each capsule 100 can include anouter casing 102 that surrounds and encloses a cavity 104. The casingitself can be an active component containing any of the above materialsand react with the internal materials or to the external stimuli. Thecavity 104 can hold an indicator material, such as a dye 106. For thepurposes of brevity, the remainder of this description will describecapsules 100 enclosing one or more dyes 106. However, it will beappreciated by a person of ordinary skill in the art that othermaterials can be sued, as described above.

The casing 102 can be configured to release the dye 106 from the cavity104 after a specified threshold is applied to the casing 102, such as aparticular pressure, temperature, light, electromagnetic, or chemicalenergy source. For example, the casing 102 can be configured so that itis breached, e.g., by cracking or fracturing, at a specified pressurethreshold.

In another example, the casing 102 can be configured to be permeable tothe dye 106, but only above a specified threshold of the dye 106 withinthe cavity 104. When the specified threshold is applied to the casing102, the casing 102 can become permeable to the dye 106 and the dye 106can be released through the casing 102.

In another example, the casing 102 of the capsule 100 can include aporous structure that can absorb and hold the dye 106, similar to asponge. The porous structure of the casing 102 can be such that the dye106 is not released from the porous structure until the specifiedthreshold is applied to the capsule 100. Alternatively, rather thanhaving a film-like casing, the capsule 100 can comprise the porousstructure substantially throughout the entire structure of the capsule100.

In yet another example, the casing 102 can divide the capsule 100 into aplurality of compartments, with each compartment containing a differentcolor constituent. Each of the color constituents, by itself, can betransparent or substantially transparent. However, when the colorconstituents mix together, a color change can occur so that the dye 106can be formed. When the specified threshold is reached, one or moreportions of the casing 102 can allow a first color constituent to mixwith one or more additional color constituents to enact a color changeso that a colored dye 106 is formed. As demonstrated above, othermechanisms for the release or exposure of the material within thecapsule can be envisioned by a person of ordinary skill in the art.

The capsules 100 can be configured so that they will be unapparent to auser before the specified threshold is applied to the capsules 100. Forexample, the material of the casing 102 can be such that the capsules100 appear to blend in with the material on which the capsules 100 areapplied. For example, if the capsules 100 are being used on a tissuemodel that is simulating a particular type of tissue, the casing 102 ofthe capsules 100 can have a color that substantially matches the colorof the tissue being simulated. In the example described above where aplurality of color constituents are separated by the casing 102 untilthe specified pressure threshold is applied, the casing 102 and thecolor constituents can be transparent or substantially transparent. Inthis example, the capsules 100 can appear to be substantially invisibleto the user until the specified threshold is reached and the capsule 100allows the color constituents to mix.

The capsules 100 can also be unapparent by having a size that would bedifficult or impossible for the human eye to distinguish. In an example,the capsules can have a size in a length direction (e.g., a diameter) offrom about _(—)100 μm to about _(—)1 cm_. Depending on the size of thecapsules 100, the density of capsules 100 at the portion of the tissuemodel to be analyzed (e.g., the number of capsules 100 or the weight ofcapsules 100 per unit area or unit volume) can be selected so that whenthe specified threshold is applied to the tissue model, the capsules 100will release a sufficient amount of the dye 106 to be detectable.

The capsules 100 can also be configured to release different dyes atdifferent thresholds to provide for tiered evaluation of the force orpressure being applied to a tissue model. For example, as shown in FIG.7C, a first subset of the capsules 100A can include a first dye 106A andcan be configured to release the first dye 106A at a first threshold,e.g., a lower pressure threshold. A second subset of the capsules 100Bcan include a second dye 106B and can be configured to release thesecond dye 106B at a second threshold, e.g., a middle pressurethreshold. A third subset of the capsules 100C can include a third dye106C and can be configured to release the third dye 106C at a thirdthreshold, e.g., a higher pressure threshold. The different thresholdscan be achieved with each type of capsule 100A, 100B, 100C, for example,by using different materials for the casing 102A, 102B, 102C of eachtype of capsule 100A, 100B, 100C that will rupture at the differentthresholds. Similarly, the casings 102A, 102B, 102C can be formed withdifferent thicknesses, or can be formed to be permeable to the dye 106A,106B, 106C at different stimuli intensities.

T differed capsules 100A, 100B, 100C can also include differentmaterials that will be distinguishable when detected. For example, thefirst dye 106A can comprise a green dye and the first capsules 100A canbe configured to release the first dye 106A when a relatively smallstimulus (e.g., a low pressure) is applied to the tissue model in orderto indicate that contact with the tissue model has been made. The seconddye 106B can comprise a yellow dye and the second capsules 100B can beconfigured to release the second dye 106B when the applied stimulus isabove a specified “warning” value at which tissue damage of the tissuebeing simulated by the tissue model can begin to occur (e.g., above anintermediate “warning” pressure threshold). The third dye 106C cancomprise a red dye and the third capsules 100C can be configured torelease the third dye 106C when the applied stimulus is above athreshold where the tissue being simulated is certain or substantiallycertain to be damaged (e.g., above a predetermined maximum allowablepressure). A larger or smaller number of thresholds can be detectedusing capsules 100 of different configurations and materials.

As described so far, the dye 106 within the capsules can be visible orcan be configured to become visible when the specified pressurethreshold is applied to the capsules 100. Visible dye 106 can providedirect feedback to a trainee to know when and where excessive pressurewas applied to the tissue model. However, the dye 106 can be configuredto be invisible, substantially invisible, or substantially visuallyunapparent to a user under normal light even after the dye 106 has beenreleased from the capsules 100. The released dye 106 can comprise alatently detectable material, such as a dye that is only visible orotherwise detectable under specific conditions. For example, thereleased dye 106 can then be made to become visible only whenilluminated under light having a specific wavelength or range ofwavelengths, such as ultraviolet (UV) light. The dye 106 can then bemade to be visible to a trainee or an evaluator after completion of themedical procedure.

The released dye 106 from the capsules 100 can comprise a material thatis sensitive to a particular wavelength or range of wavelengths oflight. In an example, the dye 106 can include an ultraviolet lightsensitive material that fluoresces when the UV-sensitive material isexposed to UV light. For the sake of brevity, the dye 106 will bedescribed as including a UV-sensitive indicator material. However, aperson of ordinary skill in the art can appreciate that materialssensitive to other wavelengths of light, such as infrared light, can beused.

While performing a specified task, such as a medical procedure, a user(e.g., a trainee) can be unaware that the dye 106 has been released fromthe capsules 100 due to the transparent nature of the dye 106 undernormal light. Following completion of a task by the user, an evaluationof his or her ability to perform the task can be made by exposing thetissue model to UV light, where the UV-sensitive dye 106, if exposed,will fluoresce, revealing that the dye 106 has been released (which canindicate that the user applied force or pressure beyond the specifiedpressure threshold).

As noted above, different capsules 100A, 100B, 100C (FIG. 7C) can beconfigured with different colored dyes 106A, 106B, 106C. Similarly, ifan initially invisible or substantially invisible, UV-sensitive dye 106is used, different capsules 100 can be configured to fluoresce in morethan one color when exposed to UV light. As described above, thedifferent capsules 100A, 100B, 100C can indicate different appliedthresholds. The different capsules 100A, 100B, 100C with differentcolored dyes 106A, 106B, 106C can also be applied to different positionson or within the tissue model, such as to indicate a first area where aparticular stimulus is acceptable, and other areas where the samestimulus would be unacceptable.

The capsules 100 can be applied to desired locations of the tissue modelor tools by any method that accurately and reliably places the capsules100. FIGS. 7A-7C show three examples of configurations for thedeployment of the capsules 100. The subject matter of the presentdescription is not limited to these particular examples, and thecapsules 100 of the present description can be implemented in otherconfigurations or structures.

FIG. 7A is a diagram of an example of a system 110 including a tissuemodel 112 and a tool 114 being used on the tissue model 112. The tool114 can be any tool that can be used for a simulated medical procedure,including, but not limited to, a cannula, a catheter, a curette, adilator, a dissecting tool, forceps, a hemostat, a laparoscopic tool, aretractor, a scalpel or other cutting tool, a speculum, an endoscope orother endoscopic tool, a suction tube, a surgical clamp, a surgicalelevator, a suture and a needle for preparing a suture, a tracheotomytool such as a tracheotomy tube, and a trocar. The tissue model 112includes a film 116 deposited or formed on an upper surface 115 of thetissue model 112. The film 116 includes the capsules 100 dispersedthroughout, wherein the capsules 100 are configured to release or exposea material, such as a dye 106, when a predetermined stimulus thresholdis applied to the capsules 100, as described above.

FIG. 7B is a diagram of another example system 120 including an exampletissue model 122 and a tool 124. Similar to the tissue model 112 and thetool 114 described above with respect to FIG. 7A, the tool 124 can beused to simulate a medical procedure on the tissue model 122. The tool124 can be any tool that can be used for a simulated medical procedure,including, but not limited to the examples of tools listed above withrespect to tool 114 in FIG. 7A. The system 120 also includes a film 126comprising capsules 100 that release dye 106 when a predeterminedstimulus threshold is applied to the capsules 100. However, rather thanbeing applied to a surface of the tissue model, as with the film 116 inFIG. 7A, the film 126 in FIG. 7B is applied to a surface 125 of the tool124.

In an example, the film 116 of FIG. 7A or the film 126 of FIG. 7B can bein the form of a pre-formed film that is applied to the surface 115, 125upon which the film 116, 126 is to be positioned. The film 116, 126 canbe adhered or otherwise attached to the surface 115, 125, such as with apressure-sensitive adhesive, a bonding adhesive, or one or morefasteners, or the film 116, 126 can be allowed to rest on the surface115, 125 with gravity holding the film 116, 126 in place. The preformedfilm 116, 126 can comprise a solid or substantially solid base material118 (in the film 116 of FIG. 7A) or base material 128 (in the film 126of FIG. 7B) that holds the capsules 100 in place within athree-dimensional structure. The base material 118, 128 can comprise anymaterial that provides for a satisfactory feel for the user. An exampleof a material of the base material 118, 128 that can be used is apolymeric material, such as a polyester-based, urethane-based, orpolyurethane-based polymer. An example of a pre-formed film that can beused as the film 116, 126 in FIG. 7A is a low-pressurepressure-indicating film sold by Pressure Metrics LLC, WhitehouseStation, N.J., USA, such as the Fujifilm Prescale 4LW (Extreme LowPressure) film.

In another example, the film 116 of FIG. 7A or the film 126 of FIG. 7Bcan be applied in the form of a paint-like coating that can be coatedonto the surface 115, 125 by a liquid-coating technique, such asbrushing on, dip coating, spin coating, and the like. The coating caninclude the capsules 100 suspended in a liquid precursor such that theliquid precursor can be applied by the desired liquid-coating technique.The liquid precursor can be configured to solidify to form a solid orsubstantially solid base material 118, 128 that supports the capsules100 in place. An example of a coating material that can be applied tothe surface 115, 125 to form the film 116, 126 are powder-basedpressure-sensitive capsules deployed in a paintable coating of siliconadhesive sold by Luna Innovations Inc., Roanoke, Va., USA.

FIG. 7C is a diagram of another example system 130 including a tissuemodel 132 and a tool 134. However, rather than incorporating capsules100 in the form of a film 116, 126, the tissue model 132 includescapsules 100A, 100B, 100C (collectively referred to herein as “capsules100”) as an additive of the tissue model 132 itself. For example, asdescribed in further detail below, the tissue model 132 can be formedfrom an organosilicate base that can include additive, wherein thecapsules 100 can be an additive that is included in the organosilicatebase. The capsules 100 can be blended with the organosilicate basematerial of the tissue model 132 prior to setting theorganosilicate-based material into a solid or substantially solid form.In an example, at least a portion of the base material of the tissuemodel 132 can be transparent or translucent to the particular wavelengthof light or range of wavelengths being reflected by the released dye106A, 106B, 106C (collectively referred to herein as “dye 106”) from thecapsules 100 (or by the wavelength of UV light that the tissue model 132is exposed to and the wavelength of light that the dye 106 fluorescesat, if an initially transparent or substantially transparentUV-sensitive dye 106 is used). The transparence or translucency to therelevant wave length of light of the dye 106 can allow for detection ofdye 106 that is released internally within the tissue model 132, butthat would not necessarily be visible at an outer surface 135 of thetissue model 132.

The tissue model system can include visual inspection and analysisequipment such as a camera or scanner coupled to a processor that cananalyze the tissue model and any released or exposed material, such as adye 106. For example, the camera or scanner can be coupled to one ormore processors, such as one or more microprocessors, digital signalprocessors (DSPs), application specific integrated circuits (ASICs),field programmable gate arrays (FPGAs), programmable logic circuitry, orthe like, either alone or in any suitable combination. The one or moreprocessors can be configured to analyze an assessment image or videocaptured by the camera or scanner in order to assess performance of aparticular medical procedure. The one or more processors can thenprovide feedback to a user regarding performance of the medicalprocedure. The feedback can be formative (e.g., training or teaching forimprovement of the user) or summative (e.g., a test or other evaluation)in nature.

In an example, the one or more processors are configured to compare oneor more images or video captured by the camera or scanner to one or morereference images or videos in order to determine a compliance of thepresent medical procedure to an ideal or desired outcome for the medicalprocedure. In an example, the reference image or video can be apredetermined color map that can be accessed by the processor to compareto the actual location of released dye 106 detected by the camera. Thecolor map can include the location of capsules 100, the colors atparticular locations, and the meaning of particular colors (e.g., ifparticular colors refer to a particular stimulus threshold).

The assessment image can be compared to the reference image via imageprocessing software that is run by the one or more processors. The imageprocessing software can allow the processor to first register theassessment image and the reference image, and then to compare registeredimages to determine a difference between the two images, and, in someexamples, to provide an assessment score. Image analysis can be used toprovide for an inexpensive and automated means of quantifying tissueinteraction measures such as peak pressure, mean pressure, or cumulativearea of crushed or otherwise damaged tissue.

The image processing software can be configured to determine anassessment score based on the comparison of the assessment image to thereference image in order to provide a quantitative measure ofperformance. In an example, the assessment score can be calculated as apercentage of the area occupied by the capsules 100 that releases orexposes the impregnated material or materials, e.g., the dye or dyes106. Other methods of determining a quantitative assessment score can beused without varying from the scope of the present disclosure. Forexample, specific areas or location of the assessment indicators can begiven a weighted score so that release of dye 106 in certain areas canresult in a lower score, e.g., a larger penalty, than in other areas.Similarly, the weighting of the score can result in a lack of releaseddye 106 in certain areas resulting in a higher score, e.g., a bonus,than in other areas. Moreover, the use of capsules 100 configured torelease dye 106 at one or more predetermined stimulus thresholds can becombined with other analysis methods, such as the uses of assessmentindicators described above with respect to FIGS. 1-6, or the use ofoptical recording of the tissue model as described below with respect toFIGS. 9-12.

The use of capsules 100, such as in one of the configurations shown inFIGS. 7A-7C, can provide several benefits over other methods forevaluation of stimuli being applied on a tissue model. First, the use ofcapsules 100 can be relatively inexpensive and relatively easy toimplement. For example, the film 116, 126 of FIGS. 7A and 7B on asurface 115 of the tissue model 112 or a surface 125 of the tool 124 canbe implemented using a relatively inexpensive pre-formed film or aliquid precursor to form the film 116 rather than the use of moreexpensive electrical or mechanical sensors. Similarly, the visualinspection and analysis described above can be incorporated into thesame camera and visual analysis processing system described above withrespect to the system 10 of FIGS. 1-5. Second, the use of capsules 100can allow the tissue model 112, 122, 132 to be designed with noelectrical sensors or mechanical sensors being present on or within thetissue model 112, 122, 132. Placing any electrical or mechanicalcomponents, devices, or systems within a tissue model that is to be usedto simulate real, live tissue can cause the tissue model to reactunrealistically. Also, it can be difficult to design a tissue model toreact realistically to applied forces while electrical or mechanicaldevices or systems are present, including electrical or mechanicalcomponents themselves, along with supporting wires, power sources, orheat sources. Therefore, the capsules 100 can allow the tissue model112, 122, 132 to be a more faithful and higher fidelity model for actualliving tissue, which does not include the physical structures ofelectrical sensors or mechanical sensors. Therefore, the tissue model112, 122, 132 incorporating capsules 100 configured to release dye 106at a prescribed stimulus threshold can provide for a more realisticsimulation experience for the user.

FIG. 8 is a flow diagram of an example method 150 of assessingperformance of a medical procedure. The method 150 can include, at 152,applying capsules configured to release dye at a predetermined stimulusthreshold, such as capsules 100 containing dye 106, to a tissue model ora tool. As described above, the capsules can be applied as a film on asurface of the tissue model or the tool, or both, or the capsules can beincorporated into the tissue model or tool, such as by being dispersedas an additive in the material that forms the tissue model or the tool.In one example, a film comprising the capsules can be deposited orformed on the surface of the tissue model or on the surface of the tool.As described above, depositing or forming the film can includepre-forming the film and then placing, and optionally adhering orfastening the pre-formed film to the surface of the tissue model or thetool. Alternatively, as described above, depositing or forming the filmcan include applying a coating material including the capsules to thesurface of the tissue model or the tool-for example via a liquid coatingmethod such as painting, spin coating, or dip coating-wherein thecoating material can then form a solid or substantially solid film thatincludes the capsules. In another example, the capsules can beincorporated into an interior of the tissue model or the tool, such asby being included as an additive to the material base prior to settingor solidifying the material base to form the tissue model or the tool.

At 154, a reference map, such as a color map, tissue of the tissue modelor the tool can be formed. As described above, the map can include thelocation of capsules 100, the colors at particular locations, and themeaning of particular colors (e.g., if particular colors refer to aparticular stimulus threshold).

At 156, an assessment image or video of the tissue model or the tool canbe taken during or after performance of the medical procedure, such asby taking a picture or video of the tissue model or the tool so that thelocation of released or exposed material can be captured. If thematerial in the capsules comprises initially invisible or substantiallyinvisible but UV-sensitive dye, then the picture or video can becaptured while the tissue model or the tool is being exposed to aparticular wavelength of light or range of wavelengths, such as UVlight, so that the released material is visible in the captured image orvideo. The assessment image or video can be analyzed, such as bycomparing to a reference, such as a reference map, at 158, and creatinga score from the comparison of the assessment image or video to thereference, at 160. The score can be a quantitative score based on one ormore measurable differences between the assessment image and thereference image, such as a percentage of the dye released from thecapsules. The score can also be provided by comparing the assessmentimage to a simulation model of the tissue that can estimate tissueoutcomes, such as scarring or other tissue damage that would be expectedbased on the location and character of the dye released.

FIGS. 9-11 demonstrate example systems for measuring deformation andforce exerted on a tissue model and for measuring pressure within thetissue model. The systems can provide for optical inspection andanalysis of the deformation of a tissue model under an applied force toprovide for real-time measurement of the deformation and movement of thestructures that form the tissue model.

FIG. 9 shows a side view of an example tissue model 200 that isconfigured for use with the optical measurement systems described below.The tissue model 200 includes a plurality of layers 202A, 202B, 202C,202D, 202E, 202F, 202G (collectively referred to herein as “layers202”). The tissue model 200 can be designed with one or more physicalproperties that are highly representative of the same physicalproperties of a live tissue that is to be simulated by the tissue model.For example, the tissue model 200 can be designed to simulate aparticular human tissue (such as an abdominal wall tissue) bysubstantially matching mechanical properties (such as viscoelasticproperties, nanoindentive properties, strain rate insensitivity,compressibility, stress-strain curves, Young's modulus, yield stress,tear point, deformability, and the like), electroconductive properties,thermoconductive properties, optical properties, chemical properties,and anisotropic properties of the native tissue.

Because the tissue model 200 can be designed to be a high-fidelityrepresentation of the properties listed above, the mechanical propertiesof the tissue model 200 are known. The known mechanical properties ofthe tissue can be used to calculate an external force 204 being exertedon the tissue model 200 based on the deformation that the tissue model200 experiences upon exertion of the force 204. The calculated force andthe observed deformation can also be used to determine the internalpressure that is being experienced by the tissue model 200.

For example, the applied force 204 in FIG. 9 can be calculated based onone or more of the known mechanical properties of the tissue model 200.Moreover, because the mechanical properties can also be known for eachof the layers 202 that make up the tissue model 200, a profile of theforce vectors showing the force profile throughout each of the layers202 can be determined based on the observed displacement of the layers202.

At least one or more of the layers 202 can be made from a transparent orsubstantially transparent material to allow light propagation throughthe transparent or substantially transparent layers 202. The tissuemodel 200 can be viewed and recorded by one or more optical devices,such as a machine-vision like camera, in order to view the deformationof the tissue model 200, and specifically the deformation of each layer202 relative to the other layers 202. The optical device can view thedeformation because of the transparent or substantially transparentmaterial of one or more of the layers 202, which allows for transmissionof light from the layers 202. The field of view of the optical device ordevices can be calibrated prior to use of the tissue model 200 in orderto establish sufficient resolution, such as down to millimeter or evensub-millimeter resolution.

FIG. 10 shows an example of a simplified system 210 that can beconfigured to analyze displacement of a tissue model 212. The exampletissue model 212 in FIG. 10 comprises a single layer, rather than themultiple layers 202 in the tissue model 200 of FIG. 9. The single-layertissue model 212 can simulate a simple tissue, such as the tissue of ablood vessel. The system 210 can include one or more cameras 214A, 214B(collectively “cameras 214” or “camera 214”) on each side of thesingle-layer tissue model 212. The first camera 214A on the first sideof the tissue model 212 can provide for deformation, force, and pressuremeasurements in one axis (with the measurements being relativelygeneralized). The second camera 214B on the second side of the tissuemodel 212 can provide the same information in another plane offset bythe thickness of the tissue model 212. The offset nature of the imagescaptured by each camera 214A, 214B provides different perspectives onthe deformation of the single-layer tissue model 212 in response to adeformation force 216 to provide for more accurate measurement ofdeformation. Alternatively, a single camera can be placed looking downan edge of the single-layer tissue model 212 (not shown) to view thedeformation from the side.

FIG. 11A shows an example of another system 220 that can be configuredto analyze displacement of a tissue model 222. FIG. 11B shows a close-upside view of the tissue model 222. Like the tissue model 200 of FIG. 9,the tissue model 222 of FIGS. 11A and 11B comprises a plurality oflayers 224A, 224B, 224C, 224D, 224E (collectively “layers 224” or “layer224”). A set of one or more cameras 226A, 226B, 226C (collectively“cameras 226” or “camera 226”) can be directed toward the tissue model222 in order to view the deformation of the tissue model 222 and thetissue model layers 224 as a result of an applied force 228, such as aforce applied from a tool.

As shown in FIG. 11B, each tissue model layer 224 can comprise a basemedium 230A, 230B, 230C, 230D, 230E (collectively “base media 230” or“base medium 230”) with an upper film 232A, 232B, 232C, 232D, 232E(collectively “upper films 232” or “upper film 232”) deposited on acorresponding base medium 230. In an example, each upper film 232 isopaque. Each upper film 232 can be a different color so that the cameras226 can be configured to more readily distinguish each particular layer224. In an example, the base media 230 can be transparent orsubstantially transparent so that the different wavelengths of lightcorresponding to the different colors of the upper films 232 will betransmitted through the base media 230. The different colors of theupper films 232 and the transparent or substantially transparent natureof the base media 230 can allow the cameras 226 to separately identifyeach specific layer 224, and thus to distinguish and determine thedeformation of each specific layer 224. The different colors from thedeformation planes of the tissue model 222 can provide for a matrix ofspectral planes and resolve multiple planes and detail from the thirdaxis (e.g., up and down through the tissue model 222 in FIGS. 11A and11B). The number of planes (e.g., the number of different wavelengths ofemanating light created by different colors) and how the light isaffected by the tissue model 222 can determine the special resolution.

In an example, the base media 230 and the upper films 232 can beconfigured so that the overall tissue model 222 has mechanicalproperties that match or substantially match corresponding mechanicalproperties of live tissue, such as human tissue, as described in moredetail below. The base media 230 and the upper films 232 can also haveoptical properties that are conducive to optical inspection fordeformation measurement and force calculation, such as base media 230that is sufficiently transparent to the light wavelengths beingtransmitted through the tissue model 222 to the cameras 226, and upperfilms 232 that are sufficiently visible and conspicuous to be detectedby the cameras 226.

Additionally, the tissue model 222 can be configured so that one or moreof the layers 224 can be in the form of a lattice structure rather thanfully solid layers. For example, a three-dimensional printer (describedin more detail below) can be used to deposit each layer 224, and one ormore layers can be deposited in a lattice form. The lattice structurescan allow for additional optical properties, such as allowing UV pumplight to propagate easily through the tissue model 222. The spatialresolution of the 3D printer can also lay down the colored line materialof the upper films 232.

The cameras 226 can be configured to capture images or video of thetissue model 222, or both. In an example, shown in FIG. 11A, each camera226 can be directed at an edge 234A, 234B, 234C (collectively “edges234” or “edge 234”) of the tissue model 222 so that the camera 226 cancapture a view showing each of the layers 224, e.g., each base mediumlayer 230 and each upper film 232. A first camera 226A can be directedtoward a first edge 234A and a second camera 226B can be directed towarda second edge 234B. Any two or more of the cameras 226A, 226B, 226C canbe used (e.g., only cameras 226A and 226B, or only cameras 226A and226C, or only cameras 226B and 226C, or additional combinationsinvolving additional cameras (not shown)). The different images capturedby cameras 226A, 226B, and 226C can provide for different perspectivesof the tissue model deformation, and thus can provide for more accuratedetermination of the location of the force 228 and the resulting forcesbeing exerted on each layer 224 of the tissue model 222. In one example,shown in FIG. 11A, the first edge 234A is on a first side of the tissuemodel 222, the second edge 234B is on a second side of the tissue model222 that opposes the first side, and the third edge 234C is on a thirdside of the tissue model 222 that is between the first edge 234A and thesecond edge 234B, such as a third or front edge 234C as shown in FIG.11A.

The cameras 226 can be connected to a processor 236, such as via one ormore communication links 238A, 238B, 238C. The processor 236 can analyzethe images or video captured by the cameras 226 and, through the use ofappropriate image or video analysis software, can identify thedeformation of each layer 224, for example in the form of a map ormatrix of deformation of the tissue model 222. As noted above, becausethe mechanical properties of the tissue model 222 are designed, andtherefore are known, the processor 236 can then calculate the forcesbeing exerted at designated points within the tissue model 222. In anexample, the processor 236 can provide a corresponding map of forcevectors within the tissue model 222 based on the known materialproperties of the base media layers 230 and the upper films 232.

An example of image capturing and analysis equipment that can be used asthe cameras 226 and the processor 236 include sensor systems developedby Brystin Research and Development, Inc., Franklin, Ohio, USA, such asthe Brystin optical gauge system. The optical gauge system can useoptical distance sensors to measure position or distance of a substrate(such as the tissue model 222). The Brystin optical gauge includes amicroprocessor data collection and management electronics board designedto simultaneously acquire and process data from up to 16 individualsensors. The sensors (e.g., cameras 226) can be arranged in anyconfiguration, such as a linear array along a side of the tissue model222, or as a circular array around the tissue model 222. Another exampleis the Brystin medical device inspection system that can scan a laserbeam and collect reflected light from the inside of a structure (e.g.,from inside the transparent layers 224 of the tissue model 222).

For purposes of illustration, one method of determining forces exertedbased on known mechanical properties will be demonstrated. However,other methods using other mechanical properties, either in addition toor in place of this illustrated method can be used. In the example,objects that quickly regain their original shape after being deformed bya force, with the molecules or atoms of their material returning to theinitial state of stable equilibrium, often obey Hooke's law ofelasticity, represented by Equation [1]:

F=kx  [1]

where F is the restoring force exerted on the tissue (e.g., in SI unitsof N (kg·m/s²), k is a constant known as the rate constant or springconstant (SI units: N/m or kg/s²), and x is the displacement of thetissue model end from its equilibrium position (SI units: m).

For a tissue model having multiple layers, such as the tissue model 222with layers 224, the tissue model 222 can be modeled as a series ofelastic (springs) layers. Defining the displacement from the equilibriumposition of the block to be x₂, Hooke's law can be modified as inEquation [2]:

F _(Block) =−k _(eq) x ₂  [2]

The displacement from the equilibrium position of the point between thetwo springs can be defined as x₁. When the force of the tissue sample isallowed to come to equilibrium, the force between each spring (e.g.,elastic layer) sums to zero, so F_(Block)=0, which allows for thesolution of x₁ according to Equations [3]-[5]:

−k ₁ x ₁ +k ₂(x ₂ −x ₁)=0  [3]

−k ₁ x ₁ −k ₂ x ₁ =−k ₂ x ₂  [4]

$\begin{matrix}{x_{1} = {\frac{k_{2}}{k + k_{2}}x_{2}}} & \lbrack 5\rbrack\end{matrix}$

The forces within the block can be added together so that the combinedcalculated force can be determined, according to Equations [6]-[10]:

$\begin{matrix}{F_{Block} = {{{- k_{2}}x_{2}} + {k_{2}x_{1}}}} & \lbrack 6\rbrack \\{F_{Block} = {{{- k_{2}}x_{2}} + {k_{2}\left( {\frac{k_{2}}{k_{1} + k_{2}}x_{2}} \right)}}} & \lbrack 7\rbrack \\{F_{Block} = {{{- k_{2}}{x_{2}\left( \frac{k_{1} + k_{2}}{k_{1} + k_{2}} \right)}} + {\frac{k_{2}^{2}}{k_{1} + k_{2}}x_{2}}}} & \lbrack 8\rbrack \\{F_{Block} = {x_{2}\left( \frac{{{- k_{1}}k_{2}} - k_{2}^{2} + k_{2}^{2}}{k_{1} + k_{2}} \right)}} & \lbrack 9\rbrack \\{F_{Block} = {x_{2}\left( \frac{k_{1}k_{2}}{k_{1} + k_{2}} \right)}} & \lbrack 10\rbrack\end{matrix}$

Equations [1]-[10] should be valid so long as the tissue model 222 andeach corresponding layer 224 is behaving within the elastic range.

In an example, the images or video captured by the camera or cameras 226are analyzed by the processor 236 in real time or near real time toallow for an interactive environment, such as an augmented realitysimulation. The processor 236 can run image capturing and analysissoftware, such as Vision Builder for Automated Inspection (VBAI)software from National Instruments Corp., Austin, Tex., USA. The VBAIsoftware can allow for acquisition and processing of images using anyNational Instruments frame grabber software, National Instrumentscompact vision system, National Instruments embedded vision system,National Instruments smart cameras, as well as other cameras or camerastandards, such as GigE vision, IEEE 1394 cameras, and USB DirectShowcameras. The VBAI software can also allow for the configuration of alarge number of machine vision tools including, but not limited to,geometric matching, optical character recognition, and particleanalysis. The VBAI software can also set up complex pass or faildecisions based on inspection results and communicate trigger andinspection results over digital input/output, serial, or Ethernetprotocol.

FIG. 12 is a flow diagram of an example method 250 of assessingperformance of a medical procedure. The method 250 can include, at 252,forming or obtaining a tissue model that includes one or more layers ofmaterial. The tissue model includes at least a portion that istransparent or substantially transparent to light, similar to the tissuemodels 200, 212, and 222 described above with respect to FIGS. 9-11. At254, mechanical material properties of the tissue model are determined,wherein the mechanical material properties are related to forces exertedon the tissue model. The mechanical properties can include, but are notlimited to, elasticity, compressibility, engineering stress, yieldstress, and modulus (such as elastic modulus or Young's modulus).

At 256, one or more images or videos are captured of the tissue modelwith one or more cameras. At 258, the one or more images or videos areused, for example by a processor, to measure or determine thedeformation of the tissue model. The determined deformation can includedetermining both a specific location of the deformation, the magnitudeof the deformation, and the direction of deformation for any location ofthe tissue model.

At 260, one or more forces being exerted on the tissue are determinedbased on the known mechanical properties and the measured or determineddeformation. Determining the one or more forces can include creating amap of force vectors that are acting within the tissue model.Determining the one or more forces can also include determining orcalculating pressure buildup within the tissue model based on the forcesand deformation that are determined.

The method 250 can also optionally include, at 262, determining anassessment score based on the one or more determined forces. Theassessment score can be based on the tissue that would be presumed to bedamaged by the force applied by the user. Scoring can also be determinedon specific locations of tissue being damaged or undamaged, with someareas being given greater weight than others.

The use of an optical force measurement system, such as the examplesystems 210, 220 of FIGS. 10 and 11, can allow the tissue model 212, 222to be designed with no electrical sensors or mechanical sensors beingpresent on or within the tissue model 212, 222. As noted above, placingany electrical or mechanical components, devices, or systems within atissue model that is to be used to simulate real, live tissue can causethe tissue model to react unrealistically. Also, it can be difficult todesign a tissue model to react realistically to applied forces whileelectrical or mechanical devices or systems are present, includingelectrical or mechanical components themselves, along with supportingwires, power sources, or heat sources. Also, the use of an optical forcemeasurement system can allow the tissue model 212, 222 to be manipulatedin any way imaginable, such as cutting, tearing, manipulating, bending,twisting, and otherwise abusing while the force sensing and measurementsystem will not be adversely affected. In contrast, systems where anelectrical or mechanical sensor is used can be adversely affected if themanipulation of the tissue model could alter operation of the sensor,such as by cutting a wire or damaging the sensor.

In an example, one or more of the systems described above (e.g., thesystem 10 of FIGS. 1-5, the system 110 of FIG. 7A, the system 120 ofFIG. 7B, the system 130 of FIG. 7C, the system 210 of FIG. 10, and thesystem 220 of FIG. 11A) can be combined with one or more computingdevices to provide for an “augmented reality” (AR) system that canprovide for augmented reality of the tissue model. For example, the oneor more assessment systems can be coupled to a peripheral computingdevice comprising a camera, such as a portable computing device (e.g., atablet computer such as an APPLE IPAD, a SAMSUNG GALAXY TAB, or a GOOGLENEXUS, or a mobile phone-type device, such as an APPLE IPHONE or IPODTOUCH, a SAMSUNG GALAXY S or GALAXY NOTE). The peripheral computingdevice can be in communication with a processor of the system (e.g., theprocessor 34 in FIG. 1 or the processor 236 in FIG. 11A), wherein thesystem processor can send information such as force or deformationmeasurements to the peripheral computing device. The camera of theperipheral computing device can then be used to take a video or seriesof images of the tissue model. The processor or the peripheral computingdevice can use the information from the system processor to alter oraugment the image taken by the peripheral computing device camera toprovide a simulation video that is displayed on the screen of theperipheral computing device. The simulation video can include simulatedvirtual reality scene of what would be expected to occur in the livetissue that the tissue model is simulating. The AR system can providefor added visual realism in addition to the mechanical realism that canbe provided by the tissue model.

The methods and systems described above can be used on any type oftissue model or tissue for which analysis of a medical procedure isdesired. Examples of tissue models that can be used with the methods andsystems of the present disclosure include, but are not limited to,animal tissue models and frozen human cadaveric tissue, and simulatedartificial tissue, such as organosilicate-based tissue models. Animaltissue models and frozen human cadaveric tissue can be used to simulatehuman tissue can have fidelity issues as well as high cost and ethicalissues, which can make animal tissue or cadaveric tissue models a poorsimulation for living tissue. The factors that contribute to thevariation in constitutive properties amongst fresh or live human tissuehave been hypothesized but poorly documented. Fresh human tissue modelsare logistically difficult to obtain, store, process and lack embeddedassessment methods for formative and summative feedback.

The physical properties that can be considered for soft tissues includehomogeneity, nonlinear large deformation, anisotropy, viscoelasticity,strain rate insensitivity and compressibility. A human tissue databasecan include tissue characteristics data that provide values forcomparison with simulator materials.

The creation of a human tissue property database can provide foraccurate constitutive computer simulation models of structures, injuryand disease. The primary components affecting the creation of artificialtissue models are material costs and supplies, accurate anatomicalmodeling, knowledge of the mechanical properties of the representedtissues, choosing the right materials, assemblage of the models in anaccurate representation of human anatomy, and model development based oneducational principals and “backwards-design” with anembedded-assessment strategy to maximize the learning.

In an example, data regarding material properties of tissue to besimulated is determined by harvesting soft-tissue specimens within 24hours of death of a subject. The specimens are warmed to bodytemperature and then subjected to uniaxial or biaxial testing todetermine viscoelastic mechanical properties. In addition,electroconductive, thermoconductive, and indentation experiments can beperformed on a plurality of different tissue types. The data is thenstratified according to gender, age, and body mass index (BMI).

In an example, data from the testing of the tissue samples is used toform a tissue database, such as a human tissue database, which can beused to guide the formulation of organosilicate base material with theobjective of tailoring the recipes of artificial tissues to match theproperties of fresh human tissue.

In an example, analyzing the similarities between human tissue materialsand simulation materials is to compare characteristics of theirstress-strain curves. The stress-strain curves can be generated by apreprogrammed routine in Excel on an MTS computer based on inputtedwidth, thickness, and initial displacement values and load vs. extensiondata.

Engineering stress is defined as a force per unit area:

$\begin{matrix}{\sigma = \frac{F}{A}} & \lbrack 11\rbrack\end{matrix}$

where F is the applied force and A is the cross sectional area. Greenstrain is defined as:

$\begin{matrix}{G = {\frac{1}{2}\frac{\left( {L_{o} - L^{2}} \right)}{L^{2}}}} & \lbrack 12\rbrack\end{matrix}$

where L₀ is the original length of the sample and L is the final lengthof the sample. The Young's modulus can be found by taking the slope ofthe stress-strain curve at the initial linear portion of the graph.Yield stress is defined as the stress at which the material begins tobreak and can be found on the stress-strain curve as the maximum stressvalue on the stress-strain curve. The corresponding strain value isdefined as the strain at yield.

The data from the human tissue database allows tailoring of theorganosilicate base material. Simulator models can be produced usingcommercially available off-the-shelf (COTS) organosilicate materials.The base material can undergo modifications to change cross-linking,electrical conductivity, thermal conductivity, reflectivity,indentation, odor, and color. Pigments and dyes can be added to theorganosilicate material to create anatomically accurate color mapping ofthe simulator model.

In an example, silicone-based materials are useful in simulation andbiomedical applications. Silicon is an element that is rarely found inits elemental form but can be found as oxides or as silicates. Silica isan oxide with formula Si_(O2) that can have amorphous or crystallinestructure. Silicates are salts or esters of silicic acid (generalformula [Si_(OX)(OH)_(4-2X]n)) that contain silicon, oxygen, and metalelements. Silicones are polymers made of silicon, oxygen, carbon, andhydrogen with repeating SiO backbone (Colas, 2005). These polymers arecreated synthetically with the addition of organic groups to thebackbone via silicon-carbon bonds. A common silicone ispolydimethylsiloxane (PDMS) with monomeric repeat unit [SiO(CH₃)₂]. Thenumber of repeat units and degree of cross-linking within the siliconepolymer can account for the different types of silicone materialsavailable for different applications. Silicones have been used inbiomedical applications because of their high biocompatibility, theirchemical inertness, and their resistance to oxidation.

In an example, the material of the tissue model can comprise platinumbased silicone-rubbers, tin cured silicone rubbers or urethane rubbers.The sources and trade names of these materials are presented in Table 1.Table 2 provides the foams and additives used in the presentapplication.

In an example, a tissue-specific organosilicate base material is formedonto the three-dimensional printed model, such as by casting,depositing, molding, and the like, or can be directly formed bythree-dimensional printing. The organosilicate base material conforms tothe details of the model to create an exact replica of the patientspecific anatomy.

In an example, organosilicate material is added in precise layers toimitate the physiologically distinct layers found in skin and otherhuman tissues. In an example, a first layer of a first organosilicatematerial is applied to the three-dimensional printed model and allowedto cure to simulate a first layer of tissue. A second layer of a secondorganosilicate material is applied to the first layer, wherein thesecond organosilicate material can be different than or the same as thefirst organosilicate material and allowed to cure to simulate a secondlayer of tissue. Subsequent layers (e.g., a third, fourth, and fifthlayer, etc.) can be added over the second layer. The layers might notall be cured in between if the layers are to be inseparable. However,substances, devices, sensors can be added between or within each layer.

In an example, one thick layer of a first organosilicate material or aplurality of thin layers of the first organosilicate material can beapplied to the three-dimensional model in order to simulate asubstantially uniform tissue structure or layer. Once the material layeror layers have been added to the desired thickness, the outer materialcan be separated from the mold and sealed.

In an example, the organosilicate base can be a soft, room temperaturevulcanized (RTV) silicone rubber with a hardness of less than 30 shores.The two-part component can be addition cured and platinum catalyzed toresult in high tear strength and flexible mold compounds. Theorganosilicate base can bond to plastics. The percentage of mixing of Aand B change depending on the application of the tissue model.

In an example, a platinum salt in portion B (OSHA PEL and ACGIHthreshold limit value 0.002 mg/m³ (as Pt)) has the following technicalspecifications.

a. Mix ratio, by weight 1A:1B b. Hardness, Shore A 10 ± 2 c. Pour time,minimum 6 min d. Demould time @ 25° C. (77° F.) 30 min e. Color offwhite translucent/Colorless f. Viscosity, mixed 15,000 cP g. Specificvolume (in3/lb) 25 h. Specific gravity @ 25° C. (77° F.)    1.10 i.Shrinkage upon cure Nil j. Flash point > 350° F.

Using an organosilicate base material, the successful creation of anartificial tissue training model has been created for a human renalartery (FIG. 13) in order to meet the specifications of the AmericanUrological Association for laparoscopic and robotic clip applying(Syverson, et al., 2011). The simulator tissue was color mapped to mimichuman renal artery and filled with artificial blood to a mean arterialpressure (MAP) of 80±2 mmHG. Solid black pigment lines and dotted blackpigment lines were added for training purposes to indicate areas forclipping and cutting respectively. The model was fitted into amechanical apparatus to mimic a beating motion.

A kidney simulator (FIG. 14) was also developed using the techniquesdescribed above. The simulator utilizes renal tissue properties, e.g.,from a human tissue database, accurate human anatomical modeling(stereolithographic prototyping) and color mapping to create realisticinternal features such as the endoluminal ureter and the calyceal kidneycollecting system. The model can be used in combination with artificialkidney stones and fluid to simulate procedures such as an ureteroscopy(FIG. 16), retrograde pyelography, urethral stent placement,nephro-lithotomy, laser and extracorporeal lithotripsy and kidney stoneextraction.

The materials used to create human tissue analogues need to meet manyspecifications in order to successfully emulate actual human tissues. Insome examples, organosilicate materials are used as the base materialfor creating artificial tissues. Commercial off the shelf (COTS)organosilicate materials can undergo repeated cycles of revision bycontinually comparing testing data of the artificial tissue to the humantissue database.

Organosilicate materials are stable and do not call for specializedstorage or shipping. These materials are cost effective and are lessexpensive compared to animal and cadaveric models. The material isdurable and can often be reused which also adds to cost-effectiveness.

The organosilicate polymer base material is mostly clear in color and iscapable of being cured in room air or within a mold. The polymer basematerial is mixed thoroughly with additives, resins, or indicators toallow for equal distribution of the base throughout the combinedmixture. The mixture is placed in a mold to form a molded sample layerby layer. Once fully cured, the mold is de-cast, and the molded sampleis coated with a talcum powder and is washed with cold water to removeexcess talcum powder.

Reflectivity is a factor in ultrasound and fluoroscopy procedures. Theorganosilicate material of the tissue models of the present disclosurehas demonstrated useful reflectivity properties with respect toultrasound and fluoroscopy. This reflectivity allows the materials to beused in simulated procedures such as ultrasound and fluoroscopy.

Possible modifications affecting viscoelastic properties include ratiochanges, chemical additives and ultraviolet (UV) light exposure. Forexample, organosilicate films that are exposed to an ultraviolet lightsource have at least a 10% or greater improvement in their mechanicalproperties (i.e., material hardness and elastic modulus) compared to theas-deposited film (U.S. Pat. No. 7,468,290). The UV light has been shownto cause increased cross-linking in the material, which can increase themodulus and decrease the elasticity (Crowe-Willoughby et al., 2009). Insome examples, the intensity and duration of UV exposure can bemodulated to provide for fine-tuning of desired mechanical properties.

The completed tissue models can be used in combination with othersubstances in order to replicate a clinical situation. Theorganosilicate based tissue models can be used in the absence ofsilicone spray and can instead be implemented with inexpensive clinicalsubstitutive artificial blood, saliva, urine, or vomit.

The uses for physiologically accurate tissue simulators are widespread.Organosilicate based materials can be subjected to extremes such ascuts, burns, gun shots, and blast pressures. They can then be repairedby the trainee as part of a simulated procedure. They can also berepaired via exposure to UV lighting, reducing their cost, andincreasing their usage.

The tissue simulators can be used independently or as hybrid modelsattached to standardized patients or confederates in trainingenvironments. The trainee is able to perform tasks such as needle sticksand suturing on the attached analogue tissues without harming thevolunteer. The combination of patient interaction and accurate tissuesimulation provides for an ideal training environment.

Examples of types of tissues that can be formed using the organosilicatebase materials of the present disclosure include, but are not limitedto; fat, connective tissues, nerve, artery, vein, muscle, tendon,ligaments, renal artery tissue, kidney tissue, ureter tissue, bladdertissue, prostate tissue, urethra tissue, bleeding aorta tissue,pyeloplasty tissue, Y/V plasty tissue, airway tissue, tongue tissue,complete hand tissue, general skin tissue, specific face skin tissue,eye tissue, brain tissue, vaginal wall, breast tissue, nasal tissue,cartilage, colon tissue, stomach tissue, liver tissue, rectum, and hearttissue.

FIGS. 15-17 show examples of specific artificial tissue training modelsin accordance with the present disclosure. The artificial tissuetraining model has been created for a human face as shown in FIGS.15A-15D. FIGS. 15A-15D also show an indicator material that has beenplaced on or within the artificial tissue that can be seen under variouslight sources, such as under an ultraviolet, or “black” light (FIGS.15A, 15B, and 15C) or under an infrared light (FIG. 15D). FIG. 16 is anillustration of animate ureter training model for endoscopy. FIG. 17 isan illustration of animate hand training model for endoscopy.

EXAMPLES Example 1

Assessment markings 16 comprising a grid 20 of assessment lines 22 wereembedded in a synthetic simulated skin tissue model 12, as best seen inFIG. 2. An assessment image 38 of the tissue model 12 and the assessmentmarkings 16 was taken and registered with a reference image 40, and thetwo images 38, 40 were compared and analyzed to determine a score forthe performance of a surgical task.

The synthetic skin tissue model 12 used for suturing exercises was anorganosilicate-based material created with reference to the Human TissueDatabase from the Center for Research in Education and SimulationTechnologies (CREST) group at the University of Minnesota. Mechanicalproperties of human tissue can allow for reference of elastic modulusamong other value markers that can be used to build a material recipethat more accurately simulates human skin.

Assessment markings 16 were integrated into the simulated skin tissuemodel 12 for use in Black Light Assessment of Surgical Technique(BLAST). The assessment markings 16 are transparent under room lightingconditions but become visible in a specified color under a UV blacklight (wavelength range 340-380 nm). The assessment markings 16 were inthe form of a grid 20 of gridlines 22 in order to capture tension,overlap, and approximation of the synthetic tissue. A set of fiveregistration points 42 were included surrounding the perimeter of thegrid lines 22. The grid 20 of the assessment markings 16 were configuredto show up as blue lines under the UV black light, while theregistration points 42 were configured to show up as red dots.

A trainee or student performed a specific suturing exercise on thesynthetic skin tissue model 12, resulting in the sutured tissue model 12shown in FIG. 3. An assessment image 38 of the sutured tissue model 12and the assessment markings 16 was captured and compared to a referenceimage 40. In one example, the reference image was created by having anexpert complete the suturing exercise and an image of the resultingsutured skin tissue model was captured as a reference image under blacklight. In another example, discussed below, the image of the unsuturedtissue model shown in FIG. 2 was used as the reference image 40.

The assessment image 38 of the trainee's sutured exercise was comparedto the reference image 40 to give the trainee feedback on his or herperformance for the suturing exercise. As described in more detailbelow, the feedback was given to the trainee in the form of an image ofthe trainee's sutured tissue overlaid on top of the reference suturedtissue as well as a quantitative assessment score.

Assessment of the trainee's performance was accomplished by isolatingthe assessment markings 16A from both the assessment image 38 and theassessment markings 16B from the reference image 40, followed byregistration of the assessment image assessment markings 16A and thereference image assessment markings 16B. It was possible to isolate theblue color of the assessment markings 16A, 16B from the red color of theregistration points 42. Image analysis of the image 38 and the referenceimage 40 was accomplished using the MATLAB software program (MathWorks,Inc., Natlick, Mass., USA). Registration of the assessment image 38 andthe reference image 40 was accomplished using the cpselect tool ofMATLAB where corresponding registration points 42 were picked manually.The cpselect function allows a MATLAB user to manually pick controlpoints of two corresponding images for registration. The imageprocessing can also be configured so that the registration points 42 arefound automatically.

The centers of the red registration points 42 were used to register theimages 38, 40 together. X and Y coordinates of the center of eachregistration point 42 was isolated by thresholding a gray scale image ofeach image 38, 40 with the isolated registration points and eroding eachof the five dots to turn them into solid objects and fill any gapswithin the five circles. The regionprops and bwlabel functions of MATLABwere used to find and label the x and y coordinates of each circle. Theregionprops function can be used to pick out the coordinates of thecenter of the thresholded circular objects that are used as registrationpoints. The regionprops function can be used to automatically find thecoordinates of the registration points without having to use thecpselect tool. The bwlabel function of MATLAB can be used to label eachof the five registration points 42.

The five coordinate pairs of the registration points 42 in the unsuturedimage (e.g., the reference image 40 of FIG. 2) were used as the basepoints and the coordinate pairs of the registration points 42 from thesutured image (e.g., the assessment image 38 of FIG. 3) were used as theinput points in a transformation of the assessment image 38 in order toregister the image 38 with the reference image. The type oftransformation used depends on the type of distortion of the assessmentimage as compared to the reference image. In this example, an affinetransformation via the cp2tform function of MATLAB was used. Thecp2tform uses affine transformation within the imtransform function ofMATLAB to spatially transform the assessment image 38 so that it isregistered with the reference image 40.

After registering the assessment image 38 with the reference image 40,the assessment markings 46A, 46B of the two images can be compared bythe image processing software to determine a quantitative score for themedical procedure. The gridlines 22A, 22B of each image 38, 40 wasthresholded a gray scale image of each image 38, 40 to isolate thegridlines 22A, 22B. The thresholded image of the assessment imagegridlines 22A was overlaid over the thresholded image of the referenceimage guidelines 22B to provide for visual feedback of the sutured skintissue model, as shown in FIG. 5. Each of the gridlines 22A, 22B can beshown differently, such as by using a first color to represent theassessment image gridlines 22A and a different second color to representthe reference image gridlines 22B. In another example, one color cancorrespond to areas of the grid 20 where the assessment image gridlines22A overlap the reference image gridlines 22B, while another color canrepresent areas where the gridlines 22A, 22B do not match up.

Quantitative feedback, such as a quantitative assessment score, can alsobe given. In the example shown in FIG. 5, a quantitative score of thepercent of pixel overlap can be used as the quantitative measure. In theexample of FIG. 5, the percent of pixel overlap is about 83.16%.

The results of the image registration and processing show that it ispossible to analyze an image of a sutured synthetic tissue and compareit to a reference image to provide visual and quantitative feedback tothe user. The results of the method of incorporating assessment linesinto the skin analog models show that it is possible for the assessmentlines to be invisible to the user while the exercise is being completed.This can be useful in providing a training environment in which the userwould be unable to use the reference lines to adjust his or hertechnique while completing the exercise. Additionally, having anunaltered piece of skin without visible assessment lines more closelyreplicates the skin of a patient seen in the clinical setting.

The method also shows that the assessment markings 16A, 16B are robustenough under a UV black light to be analyzed successfully as an image.This can be another factor for post-procedure analysis in which there ishigh ease of use and repeatability for the user when capturing images ofthe synthetic tissues.

Example 2

Two capsule products were used to form a film on a top surface of atissue model. The first film was a pre-formed polyester based FujifilmPrescale 4LW pressure sensing sheet (Pressure Metrics LLC, WhitehouseStation, N.J.) placed on top of a first sample of a tissue model. Thesecond film was a paint-on coating formed with powder based pressuresensitive capsules deployed in the coating (Luna Innovations, Roanoke,Va.) formed on a second sample of the tissue model.

The two films were tested via tissue handling simulating single graspsof bowel tissue. Samples of a tissue model of artificial single-layeredbowel tissue made from silicon rubber (LGI-10, Simulab Corporation,Seattle, Wash.) was employed and reused for all experiments.

A Mechanical Smart Endoscopic Grasper (MSEG), described in P. R. Roan,“An Instrumented Surgical Tool for Local lschemia Detection,” Pro QuestDissertations and Theses, University of Washington, USA (2011), was usedwith identical settings and calibration established in the Roan articleand in S. De, “The Grasper-Tissue Interface in Minimally InvasiveSurgery: Stress and Acute Indicators of Injury,” Department ofBioengineering, University of Washington, USA (2008). The MSEG devicewas used to apply and measure constant grasps with no overshoot.

The surface of two separate samples of the tissue model was layered witheach of the pressure sensing films. The Fujifilm Prescale 4LW was placedon top of one of the samples of the tissue model. The powder basedcapsules were suspended in a clear silicone adhesive and painted on thesurface of the artificial tissue. The test bed consisted of suspendingthe synthetic bowel from two pedestals 3 centimeters (cm) apart andapplying a series of constant, measured force levels, applied for 2minutes to each test site. The target force levels ranged from 1.5Newtons (N) to 3.5 N at increments of 0.25 N. The grasp sites werelinearly separated by 2 cm.

After at least 20 minutes had elapsed, a photo of the capsule indicatorswas taken with 14.2 megapixel (MP) resolution, 22.5 bits color depth,and 11.3 EV dynamic range digital camera under standard office lightingconditions. The resulting files were processed with ImageJ and MATLABinto a 376×400 pixel, 8-bit image individually to quantify the colorintensity in different regions via the colormap tool. The intensity waslinearly normalized to be between 0 and 1.

Table 2 shows the resulting normalized mean intensity and calculatedarea of colored pixels where the applied force measurement was providedby the MSEG tool hardware. The mean intensity was calculated over allpixel values in each grasp image, and the affected area was computed bysumming all pixel areas that exhibited values above the baselinethreshold of no applied pressure.

TABLE 2 Film-Based Applied Affected Force Mean Area (N) Intensity (mm²)1.50 0.00084 11.414 1.75 0.00126 14.569 2.00 0.00615 74.500 2.25 0.03102148.68 2.50 0.01512 96.207 2.75 0.03537 174.27 3.00 0.00712 88.401 3.250.02798 197.09 3.50 0.09971 292.29 Pearson R 0.71 (p < 0.03) 0.87 (p <0.003) Spearmanρ 0.78 (p < 0.01) 0.88 (p < 0.003)

Increasing target force levels were applied as indicated by the MSEGtool. A monotonic increase in overall intensity for each grasp in thefilm dye was expected. While there is an overall trend of increase, asindicated by Spearman's ρ>0.78 in Table 1, there were several deviationsfrom a purely monotonically increasing trend. Further investigationindicated possible slippage in the grasper force sensor, which may havecaused larger forces to be applied earlier in the sequence. Moreover,the patterns formed by the released dye show a pressure distribution inmuch finer spatial resolution (0.1 meters according to the manufacturer)than the single grasper force measurement provided by the MSEG tool,revealing that only the first row of grasper jaw “teeth” engage thetissue at a high force due to the angle of incidence. This illustratesthat even if the MESG tool force sensor was accurately calibrated, thecomputation of applied pressure distribution may be inaccurate if donewith simple assumptions about grasper area, angle of engagement, andtool-tissue orientation. The inventors suspect that the levels indicatedby the MSEG tool were less accurate than those derived from the capsuleapproach.

Limitations of the capsule approach may include time and repeatability.Currently, the dye takes time to develop its color and this change isirreversible. Thus, it may be desirable for the indicators to bedisposable and quickly replaceable.

The results of this study show that the capsule approach can provide aninexpensive, quantitative method of measuring tool-tissue pressuredistribution at a high spatial resolution.

There can be many potential uses for the techniques described in thisdisclosure. Current methods for providing feedback to students learningsuturing technique are often qualitative in nature and include oralfeedback from an expert. This type of feedback can be important fordeveloping proper instrument handling, knot tying and needle use.However, there is no quantitative or visual feedback for the studentregarding the tension environment around the wound, the amount ofoverlap created or accurate approximation of the simulated skin. Themethod of this disclosure allows for quantitative and visual feedback ofthe wound environment.

In a training situation, a student can be provided with immediatefeedback in two forms. The first form is the visual feedback incomparing his or her piece of synthetic sutured skin to the referenceimage. The use of different colors in the overlaid image can allow thestudent to clearly see the visual differences to give the studentfeedback on how to improve. The quantitative feedback given in the formof a number, such as percent of pixel overlap, can allow for recordingof progress over time as more exercises are completed. This can showimprovement or decline in the student's performance. Both the visualimage and percent pixels hit number can be stored to build a record ofprogress of a student's suturing technique. In an assessment situation,the percent of pixel overlap is a quantitative value that can be auseful metric. Various ranges of values could correspond to differentlevels of proficiency in completing a suturing task. A cut-off point canbe defined that would allow a student to pass a particular suturingtask. Analysis of these values within a group of students would allowfor comparisons to be made between a student and his or her peers.

For the purpose of demonstrating the overall concept of using BLAST andMATLAB programming, the unsutured image was used as the reference image,as described above. In more complex suturing situations, such as a Y-Vplasty, the unsutured image may not be useful as the reference image dueto the large deformation and restructuring of tissue as a result of thesuturing technique. In this case, a group of experts can perform thesuturing exercise and an average of the images collected from theexperts can be used as the reference image to which the user's image canbe compared.

Assessment line patterns other than the grid 20A, 20B described abovecan be used. Other patters may be more effective or efficient indiscriminating between levels of suturing technique. Higher lineresolution or concentration of lines around the simulated wound can alsoprove to be more effective.

To better illustrate the present systems and methods for analyzingperformance of a medical procedure, a non-limiting list of exampleembodiments is provide here:

Embodiment 1 can include subject matter (such as an apparatus, a device,a method, or one or more means for performing acts), such as can includea system for assessing performance of a procedure. The subject mattercan comprise a tissue model or a tool comprising assessment indicatorsapplied thereto, one or more image-capturing devices for capturing oneor more assessment images of the assessment indicators while or after auser performs the medical procedure, and a processor configured toanalyze the assessment indicators in the one or more assessment imagesand provide feedback to the user.

Embodiment 2 can include, or can optionally be combined with the subjectmatter of Embodiment 1, to optionally include the feedback provided tothe user comprising one or both of a cumulative score or formativefeedback.

Embodiment 3 can include, or can optionally be combined with the subjectmatter of one or any combination of Embodiments 1 and 2, to optionallyinclude the processor being configured to analyze the assessmentindicators in the one or more assessment images by comparing theassessment indicators to a reference.

Embodiment 4 can include, or can optionally be combined with the subjectmatter of one or any combination of Embodiments 1-3, to optionallyinclude the reference comprising a reference image or a reference mapcomprising reference indicators.

Embodiment 5 can include, or can optionally be combined with the subjectmatter of one or any combination of Embodiments 1-4, to optionallyinclude the processor being configured to compare the assessmentindicators in the one or more assessment images to the reference bycomparing the assessment indicators to the reference indicators in thereference image or the reference map.

Embodiment 6 can include, or can optionally be combined with the subjectmatter of one or any combination of Embodiments 1-5, to optionallyinclude the processor being configured to analyze the assessmentindicators with image processing software running on the processor.

Embodiment 7 can include, or can optionally be combined with the subjectmatter of one or any combination of Embodiments 1-6, to optionallyinclude the assessment indicators comprising a material sensitive to apredetermined wavelength of light or range of wavelengths.

Embodiment 8 can include, or can optionally be combined with the subjectmatter of one or any combination of Embodiments 1-7, to optionallyinclude the assessment indicators comprising an ultraviolet sensitivematerial.

Embodiment 9 can include, or can optionally be combined with the subjectmatter of one or any combination of Embodiments 1-8, to optionallyinclude the ultraviolent sensitive material being transparent undernormal light.

Embodiment 10 can include, or can optionally be combined with thesubject matter of one or any combination of Embodiments 1-9, tooptionally include the ultraviolet sensitive material being apolyurethane-based material.

Embodiment 11 can include, or can optionally be combined with thesubject matter of one or any combination of Embodiments 1-10, tooptionally include the one or more assessment images as comprising aseries of assessment images as a video.

Embodiment 12 can include, or can optionally be combined with thesubject matter of one or any combination of Embodiments 1-11, tooptionally include the assessment indicators comprising capsulesimpregnated with a material, wherein the capsules are configured toexpose the material upon exposure to a stimulus exceeding a stimulusthreshold.

Embodiment 13 can include, or can optionally be combined with thesubject matter of one or any combination of Embodiments 1-12, tooptionally include the stimulus comprising at least one of pressureexerted on the capsule, mechanical force exerted on the capsule, heatenergy on the capsule, electromagnetic energy on the capsule, lighthaving a predetermined wavelength or range of wavelengths emitted ontothe capsule, and a chemical species contacting the capsule.

Embodiment 14 can include, or can optionally be combined with thesubject matter of one or any combination of Embodiments 1-13, tooptionally include the material being configured to be viewable by theone or more image-capturing devices when the capsules are exposed to thestimulus source.

Embodiment 15 can include, or can optionally be combined with thesubject matter of one or any combination of Embodiments 1-14, tooptionally include the capsules being included in a film applied to asurface of the tissue model or the tool.

Embodiment 16 can include, or can optionally be combined with thesubject matter of one or any combination of Embodiments 1-15, tooptionally include the capsules being an additive within the tissuemodel or the tool.

Embodiment 17 can include, or can optionally be combined with thesubject matter of one or any combination of Embodiments 1-16, tooptionally include the tissue model or the tool not including anyelectrical sensors or mechanical sensors.

Embodiment 18 can include, or can optionally be combined with thesubject matter of one or any combination of Embodiments 1-17, to includesubject matter (such as an apparatus, a device, a method, or one or moremeans for performing acts), such as can include a system for assessingperformance of a medical procedure. The subject matter can comprise atissue model, one or more image-capturing devices each configured tocapture one or more images of the tissue model, and a processorconfigured to analyze the one or more images from the one or moreimage-capturing devices to determine a deformation of the tissue modeland determine a force exerted on the tissue model based on thedetermined deformation of the tissue model.

Embodiment 19 can include, or can optionally be combined with thesubject matter of one or any combination of Embodiments 1-18, tooptionally include the tissue model comprising at least a portion thatis transparent or substantially transparent to a particular wavelengthof light or range of wavelengths when viewed at a predetermined angle,and the one or more image-capturing devices are configured to captureone or images of at least the transparent or substantially transparentportion of the tissue model.

Embodiment 20 can include, or can optionally be combined with thesubject matter of one or any combination of Embodiments 1-19, tooptionally include the tissue model comprising a plurality of layers,each layer comprising the transparent or substantially transparentportion.

Embodiment 21 can include, or can optionally be combined with thesubject matter of one or any combination of Embodiments 1-20, tooptionally include the one or more image-capturing devices beingdirected toward one or more edges of the plurality of layers.

Embodiment 22 can include, or can optionally be combined with thesubject matter of one or any combination of Embodiments 1-21, tooptionally include each of the plurality of layers comprising atransparent or substantially transparent base medium that issubstantially transparent to a particular wavelength of light or rangeof wavelengths.

Embodiment 23 can include, or can optionally be combined with thesubject matter of one or any combination of Embodiments 1-22, tooptionally include an opaque or substantially opaque film deposited onthe base medium that is substantially opaque to the particularwavelength or range of wavelengths.

Embodiment 24 can include, or can optionally be combined with thesubject matter of one or any combination of Embodiments 1-23, tooptionally include the opaque or substantially opaque films of theplurality of layers comprising different colors.

Embodiment 25 can include, or can optionally be combined with thesubject matter of one or any combination of Embodiments 1-24, tooptionally include the processor being configured to distinguish each ofthe plurality of layers in the one or more images.

Embodiment 26 can include, or can optionally be combined with thesubject matter of one or any combination of Embodiments 1-25, tooptionally include the one or more image-capturing devices comprises afirst image-capturing device configured to capture an image of a firstposition of the transparent or substantially transparent portion of thetissue model and a second image-capturing device configured to capturean image of a second position of the transparent or substantiallytransparent portion of the tissue model.

Embodiment 27 can include, or can optionally be combined with thesubject matter of one or any combination of Embodiments 1-26, tooptionally include the processor being configured to determine the forceexerted on the tissue model based on known mechanical properties of thetissue model and the determined deformation of the tissue model.

Embodiment 28 can include, or can optionally be combined with thesubject matter of one or any combination of Embodiments 1-27, tooptionally include the tissue, the tissue model, or the tool notincluding any electrical sensors or mechanical sensors.

Embodiment 29 can include, or can optionally be combined with thesubject matter of one or any combination of Embodiments 1-28, to includesubject matter (such as an apparatus, a device, a method, or one or moremeans for performing acts), such as can include a synthetic tissue modelfor simulating a tissue for a medical procedure. The subject matter caninclude a base material and capsules applied to the base material, thecapsules being impregnated with a material, wherein the capsules areconfigured to expose the material upon exposure to a stimulus sourceexceeding a stimulus threshold.

Embodiment 30 can include, or can optionally be combined with thesubject matter of one or any combination of Embodiments 1-29, tooptionally include the stimulus source comprising at least one ofpressure exerted on the capsule, mechanical force exerted on thecapsule, heat energy on the capsule, electromagnetic energy on thecapsule, light having a predetermined wavelength or range of wavelengthsemitted onto the capsule, and a chemical species contacting the capsule.

Embodiment 31 can include, or can optionally be combined with thesubject matter of one or any combination of Embodiments 1-30, tooptionally include the material comprising at least one of one or moredyes, one or more chemical, one or more metal, and one or more pHindicators.

Embodiment 32 can include, or can optionally be combined with thesubject matter of one or any combination of Embodiments 1-31, tooptionally include the material being configured to be viewable by oneor more image-capturing devices when the capsules are exposed to thestimulus source.

Embodiment 33 can include, or can optionally be combined with thesubject matter of one or any combination of Embodiments 1-32, tooptionally include the capsules being included in a film applied to asurface of the tissue model.

Embodiment 34 can include, or can optionally be combined with thesubject matter of one or any combination of Embodiments 1-33, tooptionally include the capsules being an additive within the tissuemodel or the tool.

Embodiment 35 can include, or can optionally be combined with thesubject matter of one or any combination of Embodiments 1-34, tooptionally include the tissue model not including any electrical sensorsor mechanical sensors.

Embodiment 36 can include, or can optionally be combined with thesubject matter of one or any combination of Embodiments 1-35, to includesubject matter (such as an apparatus, a device, a method, or one or moremeans for performing acts), such as can include a method of assessingperformance of a medical procedure. The subject matter can includeapplying assessment indicators to a tissue model, or a tool, capturingone or more assessment images of the assessment indicators while orafter a user performs the medical procedure, analyzing the assessmentindicators in the one or more assessment images, and providing feedingback to a user.

Embodiment 37 can include, or can optionally be combined with thesubject matter of one or any combination of Embodiments 1-36, tooptionally include the providing of feedback to the user comprisingproviding one or both of a cumulative score or formative feedback.

Embodiment 38 can include, or can optionally be combined with thesubject matter of one or any combination of Embodiments 1-37, tooptionally include the analyzing of the assessment indicators in the oneor more assessment images comprising comparing the assessment indicatorsto a reference.

Embodiment 39 can include, or can optionally be combined with thesubject matter of one or any combination of Embodiments 1-38, tooptionally include the reference comprising a reference image or areference map comprising reference indicators.

Embodiment 40 can include, or can optionally be combined with thesubject matter of one or any combination of Embodiments 1-39, tooptionally include the comparing of the assessment indicators in the oneor more assessment images to the reference comprising comparing theassessment indicators to the reference indicators in the reference imageor the reference map.

Embodiment 41 can include, or can optionally be combined with thesubject matter of one or any combination of Embodiments 1-40, tooptionally include the analyzing of the assessment indicators comprisingdetermining one or more measurable geometric differences between theassessment indicators and the reference.

Embodiment 42 can include, or can optionally be combined with thesubject matter of one or any combination of Embodiments 1-41, tooptionally include the comparing of the assessment indicators to thereference comprising registering the assessment image with the referenceand creating an overlay of the assessment indicators of the registeredassessment image and the reference.

Embodiment 43 can include, or can optionally be combined with thesubject matter of one or any combination of Embodiments 1-42, tooptionally include the assessment indicators comprising a materialsensitive to a predetermined wavelength of light or range ofwavelengths.

Embodiment 44 can include, or can optionally be combined with thesubject matter of one or any combination of Embodiments 1-43, tooptionally include the capturing of the one or more assessment imagescomprising exposing the assessment indicators to the predeterminedwavelength or range of wavelengths.

Embodiment 45 can include, or can optionally be combined with thesubject matter of one or any combination of Embodiments 1-44, tooptionally include the assessment indicators including an ultravioletsensitive material.

Embodiment 46 can include, or can optionally be combined with thesubject matter of one or any combination of Embodiments 1-45, tooptionally include the ultraviolent sensitive material being transparentunder normal light.

Embodiment 47 can include, or can optionally be combined with thesubject matter of one or any combination of Embodiments 1-46, tooptionally include the ultraviolet sensitive material being apolyurethane-based material.

Embodiment 48 can include, or can optionally be combined with thesubject matter of one or any combination of Embodiments 1-47, tooptionally include the assessment indicators comprising capsulesimpregnated with a material, wherein the capsules are configured toexpose the material upon exposure to a stimulus source exceeding astimulus threshold.

Embodiment 49 can include, or can optionally be combined with thesubject matter of one or any combination of Embodiments 1-88, tooptionally include the capturing of the one or more assessment imagescomprising exposing the capsules to the stimulus source above thestimulus threshold.

Embodiment 50 can include, or can optionally be combined with thesubject matter of one or any combination of Embodiments 1-49, tooptionally include the stimulus source comprising at least one ofpressure exerted on the capsule, mechanical force exerted on thecapsule, heat energy on the capsule, electromagnetic energy on thecapsule, light having a predetermined wavelength or range of wavelengthsemitted onto the capsule, and a chemical species contacting the capsule.

Embodiment 51 can include, or can optionally be combined with thesubject matter of one or any combination of Embodiments 1-51, tooptionally include the material comprising at least one of one or moredyes, one or more chemical, one or more metal, and one or more pHindicators.

Embodiment 52 can include, or can optionally be combined with thesubject matter of one or any combination of Embodiments 1-51, tooptionally include the material being configured to be viewable by oneor more image-capturing devices that are configured to capture the oneor more assessment images.

Embodiment 53 can include, or can optionally be combined with thesubject matter of one or any combination of Embodiments 1-52, tooptionally include the capsules being included in a film applied to asurface of the tissue model or the tool.

Embodiment 54 can include, or can optionally be combined with thesubject matter of one or any combination of Embodiments 1-53, tooptionally include the capsules being an additive within the tissuemodel or the tool.

Embodiment 55 can include, or can optionally be combined with thesubject matter of one or any combination of Embodiments 1-54, tooptionally include the tissue model not including any electrical sensorsor mechanical sensors

Embodiment 56 can include, or can optionally be combined with thesubject matter of one or any combination of Embodiments 1-55, to includesubject matter (such as an apparatus, a device, a method, or one or moremeans for performing acts), such as can include a method of assessingperformance of a procedure. The subject matter can comprise capturingone or more images of a tissue model, analyzing the one or more imagesto determine a deformation of the tissue model, and determining a forceexerted on the tissue model based on the determined deformation of thetissue model.

Embodiment 57 can include, or can optionally be combined with thesubject matter of one or any combination of Embodiments 1-56, tooptionally include the tissue model including a portion that istransparent or substantially transparent to a particular wavelength oflight or range of wavelengths when viewed at a predetermined angle,wherein capturing the one or more images comprises capturing an image ofat least the transparent or substantially transparent portion.

Embodiment 58 can include, or can optionally be combined with thesubject matter of one or any combination of Embodiments 1-57, tooptionally include the tissue model comprising a plurality of layers,each layer comprising the transparent or substantially transparentportion.

Embodiment 59 can include, or can optionally be combined with thesubject matter of one or any combination of Embodiments 1-58, tooptionally include the one or more image-capturing devices beingdirected toward one or more edges of the plurality of layers.

Embodiment 60 can include, or can optionally be combined with thesubject matter of one or any combination of Embodiments 1-59, tooptionally include the analyzing the one or more images as comprisingdistinguishing each of the plurality of layers in the one or moreimages.

Embodiment 61 can include, or can optionally be combined with thesubject matter of one or any combination of Embodiments 1-60, tooptionally include the capturing the one or more images as comprisingcapturing a first image of a first position of the tissue model andcapturing a second image of a second position of the tissue model.

Embodiment 62 can include, or can optionally be combined with thesubject matter of one or any combination of Embodiments 1-61, tooptionally include the determining the force exerted on the tissue modelbeing based on known mechanical properties of the tissue model and thedetermined deformation of the tissue model.

Embodiment 63 can include, or can optionally be combined with thesubject matter of one or any combination of Embodiments 1-62, tooptionally include determining mechanical properties of the tissuemodel.

Embodiment 64 can include, or can optionally be combined with thesubject matter of one or any combination of Embodiments 1-63, tooptionally include determining a performance score based on thedetermined force.

The above detailed description includes references to the accompanyingdrawings, which form a part of the detailed description. The drawingsshow, by way of illustration, specific embodiments in which theinvention can be practiced. These embodiments are also referred toherein as “examples.” Such examples can include elements in addition tothose shown or described. However, the present inventors alsocontemplate examples in which only those elements shown or described areprovided. Moreover, the present inventors also contemplate examplesusing any combination or permutation of those elements shown ordescribed (or one or more aspects thereof), either with respect to aparticular example (or one or more aspects thereof), or with respect toother examples (or one or more aspects thereof) shown or describedherein.

In the event of inconsistent usages between this document and anydocuments so incorporated by reference, the usage in this documentcontrols.

In this document, the terms “a” or “an” are used, as is common in patentdocuments, to include one or more than one, independent of any otherinstances or usages of “at least one” or “one or more.” In thisdocument, the term “or” is used to refer to a nonexclusive or, such that“A or B” includes “A but not B,” “B but not A,” and “A and B,” unlessotherwise indicated. In this document, the terms “including” and “inwhich” are used as the plain-English equivalents of the respective terms“comprising” and “wherein.” Also, in the following claims, the terms“including” and “comprising” are open-ended, that is, a system, device,article, composition, formulation, or process that includes elements inaddition to those listed after such a term in a claim are still deemedto fall within the scope of that claim. Moreover, in the followingclaims, the terms “first,” “second,” and “third,” etc. are used merelyas labels, and are not intended to impose numerical requirements ontheir objects.

Method examples described herein can be machine or computer-implementedat least in part. Some examples can include a computer-readable mediumor machine-readable medium encoded with instructions operable toconfigure an electronic device to perform methods as described in theabove examples. An implementation of such methods can include code, suchas microcode, assembly language code, a higher-level language code, orthe like. Such code can include computer readable instructions forperforming various methods. The code may form portions of computerprogram products. Further, in an example, the code can be tangiblystored on one or more volatile, non-transitory, or non-volatile tangiblecomputer-readable media, such as during execution or at other times.Examples of these tangible computer-readable media can include, but arenot limited to, hard disks, removable magnetic disks, removable opticaldisks (e.g., compact disks and digital video disks), magnetic cassettes,memory cards or sticks, random access memories (RAMs), read onlymemories (ROMs), and the like.

The above description is intended to be illustrative, and notrestrictive. For example, the above-described examples (or one or moreaspects thereof) may be used in combination with each other. Otherembodiments can be used, such as by one of ordinary skill in the artupon reviewing the above description. The Abstract is provided to allowthe reader to quickly ascertain the nature of the technical disclosure.It is submitted with the understanding that it will not be used tointerpret or limit the scope or meaning of the claims. Also, in theabove Detailed Description, various features may be grouped together tostreamline the disclosure. This should not be interpreted as intendingthat an unclaimed disclosed feature is essential to any claim. Rather,inventive subject matter may lie in less than all features of aparticular disclosed embodiment. Thus, the following claims are herebyincorporated into the Detailed Description as examples or embodiments,with each claim standing on its own as a separate embodiment, and it iscontemplated that such embodiments can be combined with each other invarious combinations or permutations. The scope of the invention shouldbe determined with reference to the appended claims, along with the fullscope of equivalents to which such claims are entitled.

1. A system for assessing performance of a medical procedure, the systemcomprising: a tissue model or a tool comprising assessment indicatorsapplied thereto; one or more image-capturing devices for capturing oneor more assessment images of the assessment indicators while or after auser performs the medical procedure; and a processor configured to:analyze the assessment indicators in the one or more assessment images;and provide feedback to the user.
 2. The system of claim 1, wherein thefeedback provided to the user comprises one or both of a summative scoreor formative feedback.
 3. The system of claim 1, wherein the processoris configured to analyze the assessment indicators in the one or moreassessment images by comparing the assessment indicators to a reference.4. The system of claim 3, wherein the reference comprises a referenceimage or a reference map comprising reference indicators; and whereinthe processor is configured to compare the assessment indicators in theone or more assessment images to the reference by comparing theassessment indicators to the reference indicators in the reference imageor the reference map.
 5. (canceled)
 6. The system of claim 1, whereinthe assessment indicators comprise a material sensitive to apredetermined wavelength of light or range of wavelengths.
 7. The systemof claim 1, wherein the assessment indicators comprise capsulesimpregnated with an indicator material, wherein the capsules areconfigured to expose the indicator material upon exposure to a stimulussource exceeding a stimulus threshold.
 8. The system of claim 7, whereinthe stimulus source that causes the capsules to expose the indicatormaterial comprises at least one of pressure exerted on the capsule,mechanical force exerted on the capsule, heat energy on the capsule,electromagnetic energy on the capsule, light having a predeterminedwavelength or range of wavelengths emitted onto the capsule, and achemical species contacting the capsule.
 9. (canceled)
 10. (canceled)11. The system of claim 7, wherein the capsules are included in a filmapplied to a surface of the tissue model or the tool or the capsules arean additive within the tissue model or the tool.
 12. (canceled)
 13. Thesystem of claim 1, wherein the tissue model does not include anyelectrical sensors or mechanical sensors.
 14. A system for assessingperformance of a procedure, the system comprising: a tissue model; oneor more image-capturing devices each configured to capture one or moreimages of the tissue model; and a processor configured to: analyze theone or more images from the one or more image-capturing devices todetermine a deformation of the tissue model; and determine a forceexerted on the tissue model based on the determined deformation of thetissue model.
 15. The system of claim 14, wherein the tissue modelcomprises at least a portion that is transparent or substantiallytransparent to light viewed at a predetermined angle, and the one ormore image-capturing devices are configured to capture one or images ofat least the transparent or substantially transparent portion of thetissue model.
 16. The system of claim 15, wherein the tissue modelcomprises a plurality of layers, each layer comprising the transparentor substantially transparent portion, wherein the one or moreimage-capturing devices are directed toward one or more edges of theplurality of layers.
 17. The system of claim 16, wherein each of theplurality of layers comprises a transparent or substantially transparentbase medium and an opaque or substantially opaque film deposited on thebase medium.
 18. (canceled)
 19. The system of claim 16, wherein theprocessor is configured to distinguish each of the plurality of layersin the one or more images.
 20. The system of claim 15, wherein the oneor more image-capturing devices comprises a first image-capturing deviceconfigured to capture an image of a first position of the transparent orsubstantially transparent portion of the tissue model and a secondimage-capturing device configured to capture an image of a secondposition of the transparent or substantially transparent portion of thetissue model.
 21. (canceled)
 22. (canceled)
 23. The system of claim 1,wherein the tissue, the tissue model and the tool do not include anyelectrical sensors or mechanical sensors.
 24. A synthetic tissue modelsimulating a tissue for a medical procedure, the synthetic tissue modelcomprising: a base material; and capsules applied to the base material,the capsules being impregnated with an indicator material, wherein thecapsules are configured to expose the indicator material upon exposureto a stimulus source exceeding a stimulus threshold.
 25. The synthetictissue model of claim 24, wherein the stimulus source comprises at leastone of pressure exerted on the capsule, mechanical force exerted on thecapsule, heat energy on the capsule, electromagnetic energy on thecapsule, light having a predetermined wavelength or range of wavelengthsemitted onto the capsule, and a chemical species contacting the capsule.26. (canceled)
 27. (canceled)
 28. The synthetic tissue model of claim24, wherein the capsules are included in a film applied to a surface ofthe tissue model or the capsules are an additive within the tissue modelor the tool.
 29. The synthetic tissue model of claim 24, wherein thetissue model does not include any electrical sensors or mechanicalsensors.